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R Software Module

rwasp_partial_least_squares.wasp

Title produced by software

Partial Least Squares - Path Modeling

Date of computation

Thu, 16 Dec 2010 09:56:46 +0000

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/16/t1292493293pxta8z23zmtdvgv.htm/, Retrieved Fri, 26 Apr 2024 05:59:45 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=110785, Retrieved Fri, 26 Apr 2024 05:59:45 +0000

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IsPrivate?

No (this computation is public)

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Estimated Impact

188

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-     [Kendall tau Correlation Matrix] [Sleep in Mammals ...] [2010-03-20 10:44:59] [b98453cac15ba1066b407e146608df68]
- RMPD  [Partial Least Squares - Path Modeling] [Review of Sleep A...] [2010-05-01 17:45:35] [b98453cac15ba1066b407e146608df68]
- RMP       [Partial Least Squares - Path Modeling] [] [2010-12-16 09:56:46] [d76b387543b13b5e3afd8ff9e5fdc89f] [Current]

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0.65321251377534	0	0.81954393554187	1.6232492903979	0.47712125471966	0	0.47712125471966	0.79934054945358	0.30102999566398
1.83884909073726	3.40602894496362	3.66304097489397	2.79518458968242	0.47712125471966	0.69897000433602	0.60205999132796	0.32221929473392	0.25527250510331
1.43136376415899	1.02325245963371	2.25406445291434	2.25527250510331	0.60205999132796	0.60205999132796	0.60205999132796	0.95904139232109	-0.15490195998574
1.27875360095283	-1.69897000433602	-0.52287874528034	1.54406804435028	0	0	0	1.19865708695442	0.5910646070265
1.48287358360875	2.20411998265592	2.22788670461367	2.59328606702046	0.60205999132796	0.69897000433602	0.60205999132796	0.7160033436348	0
1.44715803134222	0.51851393987789	1.40823996531185	1.79934054945358	0	0.30102999566398	0	1.03742649794062	0.55630250076729
1.69897000433602	1.71733758272386	2.64345267648619	2.36172783601759	0	0	0	0.91907809237607	0.14612803567824
0.84509804001426	-0.36653154442041	0.80617997398389	2.04921802267018	0.69897000433602	0.60205999132796	0.60205999132796	1.04139268515823	0.17609125905568
1.47712125471966	2.66745295288995	2.62634036737504	2.44870631990508	0.69897000433602	0.69897000433602	0.69897000433602	0.50514997831991	-0.15490195998574
0.54406804435028	-1.09691001300806	0.079181246047625	1.6232492903979	0	0	0	0.79934054945358	0.32221929473392
0.77815125038364	-0.10237290870956	0.54406804435028	1.6232492903979	0.30102999566398	0.30102999566398	0.30102999566398	0.81954393554187	0.61278385671974
1.01703333929878	-0.69897000433602	0.69897000433602	2.07918124604762	0.30102999566398	0.30102999566398	0.30102999566398	0.97772360528885	0.079181246047625
1.30102999566398	1.44185217577329	2.06069784035361	2.17026171539496	0.69897000433602	0.69897000433602	0.69897000433602	0.51851393987789	-0.30102999566398
0.5910646070265	-0.92081875395238	0	1.20411998265592	0.47712125471966	0	0.30102999566398	1.04139268515823	0.53147891704226
1.61278385671974	1.92941892571429	2.51188336097887	2.49136169383427	0	0.47712125471966	0	0.67209785793572	0.17609125905568
0.95424250943932	-1	0.60205999132796	1.44715803134222	0.69897000433602	0	0.47712125471966	1.01703333929878	0.53147891704226
0.88081359228079	0.01703333929878	0.74036268949424	1.83250891270624	0.69897000433602	0.47712125471966	0.60205999132796	0.86923171973098	-0.096910013008056
1.66275783168157	2.71683772329952	2.81624129999178	2.52633927738984	0.69897000433602	0.69897000433602	0.69897000433602	0.32221929473392	-0.096910013008056
1.38021124171161	-2	-0.60205999132796	1.69897000433602	0	0	0	1.25285303097989	0.30102999566398
2	1.79239168949825	3.12057393120585	2.42651126136458	0	0	0	0.78532983501077	0.27875360095283
0.50514997831991	-1.69897000433602	-0.39794000867204	1.27875360095283	0.60205999132796	0	0.47712125471966	1.07554696139253	0.11394335230684
0.69897000433602	0.23044892137827	0.79934054945358	1.07918124604762	0.30102999566398	0	0	1.13987908640124	0.7481880270062
0.81291335664286	0.54406804435028	1.03342375548695	2.07918124604762	0.30102999566398	0	0	1.15533603746506	0.49136169383427
1.07918124604762	-0.31875876262441	1.19033169817029	2.14612803567824	0.30102999566398	0.30102999566398	0.30102999566398	1.18184358794477	0.25527250510331
1.30535136944662	1	2.06069784035361	2.23044892137827	0.60205999132796	0.60205999132796	0.60205999132796	1	-0.045757490560675
1.11394335230684	0.20951501454263	1.05690485133647	1.23044892137827	0.30102999566398	0	0.30102999566398	1.07554696139253	0.25527250510331
1.43136376415899	2.28330122870355	2.25527250510331	2.06069784035361	0.60205999132796	0.60205999132796	0.60205999132796	0.81291335664286	0.27875360095283
1.25527250510331	0.39794000867204	1.08278537031645	1.49136169383427	0.69897000433602	0.69897000433602	0.69897000433602	0.8750612633917	-0.045757490560675
0.67209785793572	-0.55284196865778	0.27875360095283	1.32221929473392	0.47712125471966	0	0.47712125471966	1.02530586526477	0.41497334797082
0.99122607569249	0.62736585659273	1.70243053644553	1.7160033436348	0	0	0	0.86923171973098	0.38021124171161
1.46239799789896	0.83250891270624	2.25285303097989	2.2148438480477	0.30102999566398	0.47712125471966	0.30102999566398	0.92427928606188	0.079181246047625
0.84509804001426	-0.1249387366083	1.0899051114394	2.35218251811136	0.30102999566398	0.30102999566398	0.30102999566398	0.75587485567249	-0.045757490560675
0.77815125038364	0.55630250076729	1.32221929473392	2.35218251811136	0.47712125471966	0.30102999566398	0.47712125471966	0.69019608002851	-0.30102999566398
1.30102999566398	1.74429298312268	2.24303804868629	2.17897694729317	0.69897000433602	0.69897000433602	0.69897000433602	0.50514997831991	-0.22184874961636
0.65321251377534	-0.045757490560675	0.41497334797082	1.77815125038364	0.30102999566398	0	0.30102999566398	1.04139268515823	0.36172783601759
0.8750612633917	0.30102999566398	1.0899051114394	2.30102999566398	0.47712125471966	0	0.47712125471966	0.69019608002851	-0.30102999566398
0.36172783601759	-1	0.39794000867204	1.66275783168157	0.47712125471966	0.30102999566398	0.30102999566398	1.12057393120585	0.41497334797082
1.38021124171161	0.6222140229663	1.76342799356294	2.32221929473392	0.60205999132796	0.47712125471966	0.60205999132796	0.98677173426624	-0.22184874961636
0.47712125471966	0.54406804435028	0.5910646070265	1.14612803567824	0.30102999566398	0	0	1.10720996964787	0.81954393554187

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	8 seconds
R Server	193.190.124.10:1001 @ 193.190.124.10:1001

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 8 seconds \tabularnewline
R Server & 193.190.124.10:1001 @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110785&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]8 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]193.190.124.10:1001 @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110785&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110785&T=0

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	8 seconds
R Server	193.190.124.10:1001 @ 193.190.124.10:1001

PARTIAL LEAST SQUARES PATH MODELING (PLS-PM)
MODEL SPECIFICATION
Number of Cases	39
Latent Variables	3
Manifest Variables	9
Scaled?	TRUE
Weighting Scheme	centroid
Bootstrapping?	TRUE
Bootstrap samples	100

\begin{tabular}{lllllllll}
\hline
PARTIAL LEAST SQUARES PATH MODELING (PLS-PM) \tabularnewline
MODEL SPECIFICATION \tabularnewline
Number of Cases & 39 \tabularnewline
Latent Variables & 3 \tabularnewline
Manifest Variables & 9 \tabularnewline
Scaled? & TRUE \tabularnewline
Weighting Scheme & centroid \tabularnewline
Bootstrapping? & TRUE \tabularnewline
Bootstrap samples & 100 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110785&T=1

[TABLE]
[ROW][C]PARTIAL LEAST SQUARES PATH MODELING (PLS-PM)[/C][/ROW]
[ROW][C]MODEL SPECIFICATION[/C][/ROW]
[ROW][C]Number of Cases[/C][C]39[/C][/ROW]
[ROW][C]Latent Variables[/C][C]3[/C][/ROW]
[ROW][C]Manifest Variables[/C][C]9[/C][/ROW]
[ROW][C]Scaled?[/C][C]TRUE[/C][/ROW]
[ROW][C]Weighting Scheme[/C][C]centroid[/C][/ROW]
[ROW][C]Bootstrapping?[/C][C]TRUE[/C][/ROW]
[ROW][C]Bootstrap samples[/C][C]100[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110785&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110785&T=1

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

PARTIAL LEAST SQUARES PATH MODELING (PLS-PM)
MODEL SPECIFICATION
Number of Cases	39
Latent Variables	3
Manifest Variables	9
Scaled?	TRUE
Weighting Scheme	centroid
Bootstrapping?	TRUE
Bootstrap samples	100

BLOCKS DEFINITION
Block	Type	NMVs	Mode
ecol	Exogenous	3	Reflective
const	Endogenous	4	Reflective
sleep	Endogenous	2	Reflective

\begin{tabular}{lllllllll}
\hline
BLOCKS DEFINITION \tabularnewline
Block & Type & NMVs & Mode \tabularnewline
ecol & Exogenous & 3 & Reflective \tabularnewline
const & Endogenous & 4 & Reflective \tabularnewline
sleep & Endogenous & 2 & Reflective \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110785&T=2

[TABLE]
[ROW][C]BLOCKS DEFINITION[/C][/ROW]
[ROW][C]Block[/C][C]Type[/C][C]NMVs[/C][C]Mode[/C][/ROW]
[ROW][C]ecol[/C][C]Exogenous[/C][C]3[/C][C]Reflective[/C][/ROW]
[ROW][C]const[/C][C]Endogenous[/C][C]4[/C][C]Reflective[/C][/ROW]
[ROW][C]sleep[/C][C]Endogenous[/C][C]2[/C][C]Reflective[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110785&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110785&T=2

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

BLOCKS DEFINITION
Block	Type	NMVs	Mode
ecol	Exogenous	3	Reflective
const	Endogenous	4	Reflective
sleep	Endogenous	2	Reflective

BLOCKS UNIDIMENSIONALITY
Block	Type.measure	MVs	eig.1st	eig.2nd	C.alpha	DG.rho
ecol	Reflective	3	2.49392667785567	0.44918051829769	0.896300070317852	0.936385726725812
const	Reflective	4	3.28523164521364	0.354740490703899	0.926598168727977	0.948298634274641
sleep	Reflective	2	1.55800616818027	0.441993831819727	0.716308034687713	0.875774855093694

\begin{tabular}{lllllllll}
\hline
BLOCKS UNIDIMENSIONALITY \tabularnewline
Block & Type.measure & MVs & eig.1st & eig.2nd & C.alpha & DG.rho \tabularnewline
ecol & Reflective & 3 & 2.49392667785567 & 0.44918051829769 & 0.896300070317852 & 0.936385726725812 \tabularnewline
const & Reflective & 4 & 3.28523164521364 & 0.354740490703899 & 0.926598168727977 & 0.948298634274641 \tabularnewline
sleep & Reflective & 2 & 1.55800616818027 & 0.441993831819727 & 0.716308034687713 & 0.875774855093694 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110785&T=3

[TABLE]
[ROW][C]BLOCKS UNIDIMENSIONALITY[/C][/ROW]
[ROW][C]Block[/C][C]Type.measure[/C][C]MVs[/C][C]eig.1st[/C][C]eig.2nd[/C][C]C.alpha[/C][C]DG.rho[/C][/ROW]
[ROW][C]ecol[/C][C]Reflective[/C][C]3[/C][C]2.49392667785567[/C][C]0.44918051829769[/C][C]0.896300070317852[/C][C]0.936385726725812[/C][/ROW]
[ROW][C]const[/C][C]Reflective[/C][C]4[/C][C]3.28523164521364[/C][C]0.354740490703899[/C][C]0.926598168727977[/C][C]0.948298634274641[/C][/ROW]
[ROW][C]sleep[/C][C]Reflective[/C][C]2[/C][C]1.55800616818027[/C][C]0.441993831819727[/C][C]0.716308034687713[/C][C]0.875774855093694[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110785&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110785&T=3

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

BLOCKS UNIDIMENSIONALITY
Block	Type.measure	MVs	eig.1st	eig.2nd	C.alpha	DG.rho
ecol	Reflective	3	2.49392667785567	0.44918051829769	0.896300070317852	0.936385726725812
const	Reflective	4	3.28523164521364	0.354740490703899	0.926598168727977	0.948298634274641
sleep	Reflective	2	1.55800616818027	0.441993831819727	0.716308034687713	0.875774855093694

OUTER MODEL
Block	weights	std.loads	communal	redundan
ecol
logP	0.2266	0.8676	0.7528	0
logS	0.5046	0.9015	0.8127	0
logD	0.3709	0.9397	0.8831	0
const
logL	0.1927	0.8382	0.7026	0.1564
logWb	0.301	0.9266	0.8587	0.1912
logWbr	0.2924	0.97	0.9409	0.2095
logtg	0.3134	0.8808	0.7757	0.1727
sleep
logSWS	0.5879	0.8919	0.7956	0.5167
logPS	0.5449	0.8729	0.762	0.4949

\begin{tabular}{lllllllll}
\hline
OUTER MODEL \tabularnewline
Block & weights & std.loads & communal & redundan \tabularnewline
ecol \tabularnewline
logP & 0.2266 & 0.8676 & 0.7528 & 0 \tabularnewline
logS & 0.5046 & 0.9015 & 0.8127 & 0 \tabularnewline
logD & 0.3709 & 0.9397 & 0.8831 & 0 \tabularnewline
const \tabularnewline
logL & 0.1927 & 0.8382 & 0.7026 & 0.1564 \tabularnewline
logWb & 0.301 & 0.9266 & 0.8587 & 0.1912 \tabularnewline
logWbr & 0.2924 & 0.97 & 0.9409 & 0.2095 \tabularnewline
logtg & 0.3134 & 0.8808 & 0.7757 & 0.1727 \tabularnewline
sleep \tabularnewline
logSWS & 0.5879 & 0.8919 & 0.7956 & 0.5167 \tabularnewline
logPS & 0.5449 & 0.8729 & 0.762 & 0.4949 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110785&T=4

[TABLE]
[ROW][C]OUTER MODEL[/C][/ROW]
[ROW][C]Block[/C][C]weights[/C][C]std.loads[/C][C]communal[/C][C]redundan[/C][/ROW]
[ROW][C]ecol[/C][/ROW]
[ROW][C]logP[/C][C]0.2266[/C][C]0.8676[/C][C]0.7528[/C][C]0[/C][/ROW]
[ROW][C]logS[/C][C]0.5046[/C][C]0.9015[/C][C]0.8127[/C][C]0[/C][/ROW]
[ROW][C]logD[/C][C]0.3709[/C][C]0.9397[/C][C]0.8831[/C][C]0[/C][/ROW]
[ROW][C]const[/C][/ROW]
[ROW][C]logL[/C][C]0.1927[/C][C]0.8382[/C][C]0.7026[/C][C]0.1564[/C][/ROW]
[ROW][C]logWb[/C][C]0.301[/C][C]0.9266[/C][C]0.8587[/C][C]0.1912[/C][/ROW]
[ROW][C]logWbr[/C][C]0.2924[/C][C]0.97[/C][C]0.9409[/C][C]0.2095[/C][/ROW]
[ROW][C]logtg[/C][C]0.3134[/C][C]0.8808[/C][C]0.7757[/C][C]0.1727[/C][/ROW]
[ROW][C]sleep[/C][/ROW]
[ROW][C]logSWS[/C][C]0.5879[/C][C]0.8919[/C][C]0.7956[/C][C]0.5167[/C][/ROW]
[ROW][C]logPS[/C][C]0.5449[/C][C]0.8729[/C][C]0.762[/C][C]0.4949[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110785&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110785&T=4

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

OUTER MODEL
Block	weights	std.loads	communal	redundan
ecol
logP	0.2266	0.8676	0.7528	0
logS	0.5046	0.9015	0.8127	0
logD	0.3709	0.9397	0.8831	0
const
logL	0.1927	0.8382	0.7026	0.1564
logWb	0.301	0.9266	0.8587	0.1912
logWbr	0.2924	0.97	0.9409	0.2095
logtg	0.3134	0.8808	0.7757	0.1727
sleep
logSWS	0.5879	0.8919	0.7956	0.5167
logPS	0.5449	0.8729	0.762	0.4949

CORRELATIONS BETWEEN MVs AND LVs
Block	ecol	const	sleep
ecol
logP	0.8676	0.1287	-0.4639
logS	0.9015	0.6488	-0.6703
logD	0.9397	0.3109	-0.6589
const
logL	0.274	0.8382	-0.4481
logWb	0.4876	0.9266	-0.64
logWbr	0.4507	0.97	-0.6448
logtg	0.4484	0.8808	-0.7261
sleep
logSWS	-0.5548	-0.7105	0.8919
logPS	-0.6635	-0.5089	0.8729

\begin{tabular}{lllllllll}
\hline
CORRELATIONS BETWEEN MVs AND LVs \tabularnewline
Block & ecol & const & sleep \tabularnewline
ecol \tabularnewline
logP & 0.8676 & 0.1287 & -0.4639 \tabularnewline
logS & 0.9015 & 0.6488 & -0.6703 \tabularnewline
logD & 0.9397 & 0.3109 & -0.6589 \tabularnewline
const \tabularnewline
logL & 0.274 & 0.8382 & -0.4481 \tabularnewline
logWb & 0.4876 & 0.9266 & -0.64 \tabularnewline
logWbr & 0.4507 & 0.97 & -0.6448 \tabularnewline
logtg & 0.4484 & 0.8808 & -0.7261 \tabularnewline
sleep \tabularnewline
logSWS & -0.5548 & -0.7105 & 0.8919 \tabularnewline
logPS & -0.6635 & -0.5089 & 0.8729 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110785&T=5

[TABLE]
[ROW][C]CORRELATIONS BETWEEN MVs AND LVs[/C][/ROW]
[ROW][C]Block[/C][C]ecol[/C][C]const[/C][C]sleep[/C][/ROW]
[ROW][C]ecol[/C][/ROW]
[ROW][C]logP[/C][C]0.8676[/C][C]0.1287[/C][C]-0.4639[/C][/ROW]
[ROW][C]logS[/C][C]0.9015[/C][C]0.6488[/C][C]-0.6703[/C][/ROW]
[ROW][C]logD[/C][C]0.9397[/C][C]0.3109[/C][C]-0.6589[/C][/ROW]
[ROW][C]const[/C][/ROW]
[ROW][C]logL[/C][C]0.274[/C][C]0.8382[/C][C]-0.4481[/C][/ROW]
[ROW][C]logWb[/C][C]0.4876[/C][C]0.9266[/C][C]-0.64[/C][/ROW]
[ROW][C]logWbr[/C][C]0.4507[/C][C]0.97[/C][C]-0.6448[/C][/ROW]
[ROW][C]logtg[/C][C]0.4484[/C][C]0.8808[/C][C]-0.7261[/C][/ROW]
[ROW][C]sleep[/C][/ROW]
[ROW][C]logSWS[/C][C]-0.5548[/C][C]-0.7105[/C][C]0.8919[/C][/ROW]
[ROW][C]logPS[/C][C]-0.6635[/C][C]-0.5089[/C][C]0.8729[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110785&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110785&T=5

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

CORRELATIONS BETWEEN MVs AND LVs
Block	ecol	const	sleep
ecol
logP	0.8676	0.1287	-0.4639
logS	0.9015	0.6488	-0.6703
logD	0.9397	0.3109	-0.6589
const
logL	0.274	0.8382	-0.4481
logWb	0.4876	0.9266	-0.64
logWbr	0.4507	0.97	-0.6448
logtg	0.4484	0.8808	-0.7261
sleep
logSWS	-0.5548	-0.7105	0.8919
logPS	-0.6635	-0.5089	0.8729

INNER MODEL
Block	Concept	Value
S2
1	R2	0.2226
2	Intercept	0
3	path_S1	0.4718
S3
1	R2	0.6495
2	Intercept	0
3	path_S1	-0.4628
4	path_S2	-0.4767

\begin{tabular}{lllllllll}
\hline
INNER MODEL \tabularnewline
Block & Concept & Value \tabularnewline
S2 \tabularnewline
1 & R2 & 0.2226 \tabularnewline
2 & Intercept & 0 \tabularnewline
3 & path_S1 & 0.4718 \tabularnewline
S3 \tabularnewline
1 & R2 & 0.6495 \tabularnewline
2 & Intercept & 0 \tabularnewline
3 & path_S1 & -0.4628 \tabularnewline
4 & path_S2 & -0.4767 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110785&T=6

[TABLE]
[ROW][C]INNER MODEL[/C][/ROW]
[ROW][C]Block[/C][C]Concept[/C][C]Value[/C][/ROW]
[ROW][C]S2[/C][/ROW]
[ROW][C]1[/C][C]R2[/C][C]0.2226[/C][/ROW]
[ROW][C]2[/C][C]Intercept[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]path_S1[/C][C]0.4718[/C][/ROW]
[ROW][C]S3[/C][/ROW]
[ROW][C]1[/C][C]R2[/C][C]0.6495[/C][/ROW]
[ROW][C]2[/C][C]Intercept[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]path_S1[/C][C]-0.4628[/C][/ROW]
[ROW][C]4[/C][C]path_S2[/C][C]-0.4767[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110785&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110785&T=6

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

INNER MODEL
Block	Concept	Value
S2
1	R2	0.2226
2	Intercept	0
3	path_S1	0.4718
S3
1	R2	0.6495
2	Intercept	0
3	path_S1	-0.4628
4	path_S2	-0.4767

CORRELATIONS BETWEEN LVs
	ecol	const	sleep
ecol	1	0.4718	-0.6877
const	0.4718	1	-0.695
sleep	-0.6877	-0.695	1

\begin{tabular}{lllllllll}
\hline
CORRELATIONS BETWEEN LVs \tabularnewline
 & ecol & const & sleep \tabularnewline
ecol & 1 & 0.4718 & -0.6877 \tabularnewline
const & 0.4718 & 1 & -0.695 \tabularnewline
sleep & -0.6877 & -0.695 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110785&T=7

[TABLE]
[ROW][C]CORRELATIONS BETWEEN LVs[/C][/ROW]
[ROW][C][/C][C]ecol[/C][C]const[/C][C]sleep[/C][/ROW]
[ROW][C]ecol[/C][C]1[/C][C]0.4718[/C][C]-0.6877[/C][/ROW]
[ROW][C]const[/C][C]0.4718[/C][C]1[/C][C]-0.695[/C][/ROW]
[ROW][C]sleep[/C][C]-0.6877[/C][C]-0.695[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110785&T=7

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110785&T=7

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

CORRELATIONS BETWEEN LVs
	ecol	const	sleep
ecol	1	0.4718	-0.6877
const	0.4718	1	-0.695
sleep	-0.6877	-0.695	1

SUMMARY INNER MODEL
	LV.Type	Measure	MVs	R.square	Av.Commu	Av.Redun	AVE
ecol	Exogen	Rflct	3	0	0.8162	0	0.816
const	Endogen	Rflct	4	0.2226	0.8195	0.1824	0.819
sleep	Endogen	Rflct	2	0.6495	0.7788	0.5058	0.779

\begin{tabular}{lllllllll}
\hline
SUMMARY INNER MODEL \tabularnewline
 & LV.Type & Measure & MVs & R.square & Av.Commu & Av.Redun & AVE \tabularnewline
ecol & Exogen & Rflct & 3 & 0 & 0.8162 & 0 & 0.816 \tabularnewline
const & Endogen & Rflct & 4 & 0.2226 & 0.8195 & 0.1824 & 0.819 \tabularnewline
sleep & Endogen & Rflct & 2 & 0.6495 & 0.7788 & 0.5058 & 0.779 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110785&T=8

[TABLE]
[ROW][C]SUMMARY INNER MODEL[/C][/ROW]
[ROW][C][/C][C]LV.Type[/C][C]Measure[/C][C]MVs[/C][C]R.square[/C][C]Av.Commu[/C][C]Av.Redun[/C][C]AVE[/C][/ROW]
[ROW][C]ecol[/C][C]Exogen[/C][C]Rflct[/C][C]3[/C][C]0[/C][C]0.8162[/C][C]0[/C][C]0.816[/C][/ROW]
[ROW][C]const[/C][C]Endogen[/C][C]Rflct[/C][C]4[/C][C]0.2226[/C][C]0.8195[/C][C]0.1824[/C][C]0.819[/C][/ROW]
[ROW][C]sleep[/C][C]Endogen[/C][C]Rflct[/C][C]2[/C][C]0.6495[/C][C]0.7788[/C][C]0.5058[/C][C]0.779[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110785&T=8

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110785&T=8

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

SUMMARY INNER MODEL
	LV.Type	Measure	MVs	R.square	Av.Commu	Av.Redun	AVE
ecol	Exogen	Rflct	3	0	0.8162	0	0.816
const	Endogen	Rflct	4	0.2226	0.8195	0.1824	0.819
sleep	Endogen	Rflct	2	0.6495	0.7788	0.5058	0.779

GOODNESS-OF-FIT
GoF	Value
Absolute	0.594072491071591
Relative	0.769531486764
Outer.mod	0.996540232339925
Inner.mod	0.772203130180808

\begin{tabular}{lllllllll}
\hline
GOODNESS-OF-FIT \tabularnewline
GoF & Value \tabularnewline
Absolute & 0.594072491071591 \tabularnewline
Relative & 0.769531486764 \tabularnewline
Outer.mod & 0.996540232339925 \tabularnewline
Inner.mod & 0.772203130180808 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110785&T=9

[TABLE]
[ROW][C]GOODNESS-OF-FIT[/C][/ROW]
[ROW][C]GoF[/C][C]Value[/C][/ROW]
[ROW][C]Absolute[/C][C]0.594072491071591[/C][/ROW]
[ROW][C]Relative[/C][C]0.769531486764[/C][/ROW]
[ROW][C]Outer.mod[/C][C]0.996540232339925[/C][/ROW]
[ROW][C]Inner.mod[/C][C]0.772203130180808[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110785&T=9

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110785&T=9

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

GOODNESS-OF-FIT
GoF	Value
Absolute	0.594072491071591
Relative	0.769531486764
Outer.mod	0.996540232339925
Inner.mod	0.772203130180808

TOTAL EFFECTS
relationships	dir.effect	ind.effect	tot.effect
S1->S2	0.47183687754145	0	0.47183687754145
S1->S3	-0.462761043658846	-0.224904184530796	-0.687665228189642
S2->S3	-0.476656648167647	0	-0.476656648167647

\begin{tabular}{lllllllll}
\hline
TOTAL EFFECTS \tabularnewline
relationships & dir.effect & ind.effect & tot.effect \tabularnewline
S1->S2 & 0.47183687754145 & 0 & 0.47183687754145 \tabularnewline
S1->S3 & -0.462761043658846 & -0.224904184530796 & -0.687665228189642 \tabularnewline
S2->S3 & -0.476656648167647 & 0 & -0.476656648167647 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110785&T=10

[TABLE]
[ROW][C]TOTAL EFFECTS[/C][/ROW]
[ROW][C]relationships[/C][C]dir.effect[/C][C]ind.effect[/C][C]tot.effect[/C][/ROW]
[ROW][C]S1->S2[/C][C]0.47183687754145[/C][C]0[/C][C]0.47183687754145[/C][/ROW]
[ROW][C]S1->S3[/C][C]-0.462761043658846[/C][C]-0.224904184530796[/C][C]-0.687665228189642[/C][/ROW]
[ROW][C]S2->S3[/C][C]-0.476656648167647[/C][C]0[/C][C]-0.476656648167647[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110785&T=10

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110785&T=10

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

TOTAL EFFECTS
relationships	dir.effect	ind.effect	tot.effect
S1->S2	0.47183687754145	0	0.47183687754145
S1->S3	-0.462761043658846	-0.224904184530796	-0.687665228189642
S2->S3	-0.476656648167647	0	-0.476656648167647

BOOTSTRAP VALIDATION - WEIGHTS
	Original	Mean.Boot	Std.Error	perc.05	perc.95
logP	0.226611731207995	0.21993939256954	0.0666469632019318	0.0877299783497136	0.289896903312728
logS	0.50455510986497	0.512302217814878	0.0888174060094197	0.401911069903199	0.686050847699033
logD	0.370882038453552	0.366430085612776	0.0234730305972253	0.327472204322232	0.403365952329214
logL	0.192654172241961	0.180815076440143	0.0463588536646802	0.0914044961024064	0.238062667205845
logWb	0.300965281469565	0.305147698644337	0.0303783822450857	0.256590290062959	0.353726198814615
logWbr	0.292358061358382	0.291803159035632	0.0259341683346686	0.247658309134176	0.334920251701308
logtg	0.313422150013469	0.31964302086788	0.036270798702301	0.27491386109854	0.382820403966177
logSWS	0.587916401400275	0.58404996511541	0.0586606260589326	0.500224428806398	0.681061322472302
logPS	0.544852711813177	0.549981699606979	0.0501176618082805	0.473591470674297	0.633974071998176

\begin{tabular}{lllllllll}
\hline
BOOTSTRAP VALIDATION - WEIGHTS \tabularnewline
 & Original & Mean.Boot & Std.Error & perc.05 & perc.95 \tabularnewline
logP & 0.226611731207995 & 0.21993939256954 & 0.0666469632019318 & 0.0877299783497136 & 0.289896903312728 \tabularnewline
logS & 0.50455510986497 & 0.512302217814878 & 0.0888174060094197 & 0.401911069903199 & 0.686050847699033 \tabularnewline
logD & 0.370882038453552 & 0.366430085612776 & 0.0234730305972253 & 0.327472204322232 & 0.403365952329214 \tabularnewline
logL & 0.192654172241961 & 0.180815076440143 & 0.0463588536646802 & 0.0914044961024064 & 0.238062667205845 \tabularnewline
logWb & 0.300965281469565 & 0.305147698644337 & 0.0303783822450857 & 0.256590290062959 & 0.353726198814615 \tabularnewline
logWbr & 0.292358061358382 & 0.291803159035632 & 0.0259341683346686 & 0.247658309134176 & 0.334920251701308 \tabularnewline
logtg & 0.313422150013469 & 0.31964302086788 & 0.036270798702301 & 0.27491386109854 & 0.382820403966177 \tabularnewline
logSWS & 0.587916401400275 & 0.58404996511541 & 0.0586606260589326 & 0.500224428806398 & 0.681061322472302 \tabularnewline
logPS & 0.544852711813177 & 0.549981699606979 & 0.0501176618082805 & 0.473591470674297 & 0.633974071998176 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110785&T=11

[TABLE]
[ROW][C]BOOTSTRAP VALIDATION - WEIGHTS[/C][/ROW]
[ROW][C][/C][C]Original[/C][C]Mean.Boot[/C][C]Std.Error[/C][C]perc.05[/C][C]perc.95[/C][/ROW]
[ROW][C]logP[/C][C]0.226611731207995[/C][C]0.21993939256954[/C][C]0.0666469632019318[/C][C]0.0877299783497136[/C][C]0.289896903312728[/C][/ROW]
[ROW][C]logS[/C][C]0.50455510986497[/C][C]0.512302217814878[/C][C]0.0888174060094197[/C][C]0.401911069903199[/C][C]0.686050847699033[/C][/ROW]
[ROW][C]logD[/C][C]0.370882038453552[/C][C]0.366430085612776[/C][C]0.0234730305972253[/C][C]0.327472204322232[/C][C]0.403365952329214[/C][/ROW]
[ROW][C]logL[/C][C]0.192654172241961[/C][C]0.180815076440143[/C][C]0.0463588536646802[/C][C]0.0914044961024064[/C][C]0.238062667205845[/C][/ROW]
[ROW][C]logWb[/C][C]0.300965281469565[/C][C]0.305147698644337[/C][C]0.0303783822450857[/C][C]0.256590290062959[/C][C]0.353726198814615[/C][/ROW]
[ROW][C]logWbr[/C][C]0.292358061358382[/C][C]0.291803159035632[/C][C]0.0259341683346686[/C][C]0.247658309134176[/C][C]0.334920251701308[/C][/ROW]
[ROW][C]logtg[/C][C]0.313422150013469[/C][C]0.31964302086788[/C][C]0.036270798702301[/C][C]0.27491386109854[/C][C]0.382820403966177[/C][/ROW]
[ROW][C]logSWS[/C][C]0.587916401400275[/C][C]0.58404996511541[/C][C]0.0586606260589326[/C][C]0.500224428806398[/C][C]0.681061322472302[/C][/ROW]
[ROW][C]logPS[/C][C]0.544852711813177[/C][C]0.549981699606979[/C][C]0.0501176618082805[/C][C]0.473591470674297[/C][C]0.633974071998176[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110785&T=11

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110785&T=11

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

BOOTSTRAP VALIDATION - WEIGHTS
	Original	Mean.Boot	Std.Error	perc.05	perc.95
logP	0.226611731207995	0.21993939256954	0.0666469632019318	0.0877299783497136	0.289896903312728
logS	0.50455510986497	0.512302217814878	0.0888174060094197	0.401911069903199	0.686050847699033
logD	0.370882038453552	0.366430085612776	0.0234730305972253	0.327472204322232	0.403365952329214
logL	0.192654172241961	0.180815076440143	0.0463588536646802	0.0914044961024064	0.238062667205845
logWb	0.300965281469565	0.305147698644337	0.0303783822450857	0.256590290062959	0.353726198814615
logWbr	0.292358061358382	0.291803159035632	0.0259341683346686	0.247658309134176	0.334920251701308
logtg	0.313422150013469	0.31964302086788	0.036270798702301	0.27491386109854	0.382820403966177
logSWS	0.587916401400275	0.58404996511541	0.0586606260589326	0.500224428806398	0.681061322472302
logPS	0.544852711813177	0.549981699606979	0.0501176618082805	0.473591470674297	0.633974071998176

BOOTSTRAP VALIDATION - LOADINGS
	Original	Mean.Boot	Std.Error	perc.05	perc.95
logP	0.867637144235964	0.859818792721442	0.0686421329199473	0.757151341090742	0.93396984348992
logS	0.90148243160283	0.908250845896857	0.0275775829472729	0.866873235324142	0.955396507197371
logD	0.939748063343516	0.930432999415067	0.0421729871938867	0.850186126043246	0.975845241164157
logL	0.838196412672888	0.821442344494607	0.0909881270674692	0.644424208595763	0.929451769448314
logWb	0.926642148966324	0.928637838888554	0.0268411017900529	0.87712941777375	0.961680675047155
logWbr	0.969982738285346	0.96974957074225	0.00959795870638334	0.955880946339725	0.983451402259195
logtg	0.880756436094418	0.8810885944584	0.0277777317291189	0.837741446817982	0.918791075124928
logSWS	0.891947575341777	0.889541362503736	0.0364344739797181	0.826267554832962	0.932670599868892
logPS	0.87291369016888	0.872070364167138	0.0508496457296118	0.775724271361718	0.927285650635181

\begin{tabular}{lllllllll}
\hline
BOOTSTRAP VALIDATION - LOADINGS \tabularnewline
 & Original & Mean.Boot & Std.Error & perc.05 & perc.95 \tabularnewline
logP & 0.867637144235964 & 0.859818792721442 & 0.0686421329199473 & 0.757151341090742 & 0.93396984348992 \tabularnewline
logS & 0.90148243160283 & 0.908250845896857 & 0.0275775829472729 & 0.866873235324142 & 0.955396507197371 \tabularnewline
logD & 0.939748063343516 & 0.930432999415067 & 0.0421729871938867 & 0.850186126043246 & 0.975845241164157 \tabularnewline
logL & 0.838196412672888 & 0.821442344494607 & 0.0909881270674692 & 0.644424208595763 & 0.929451769448314 \tabularnewline
logWb & 0.926642148966324 & 0.928637838888554 & 0.0268411017900529 & 0.87712941777375 & 0.961680675047155 \tabularnewline
logWbr & 0.969982738285346 & 0.96974957074225 & 0.00959795870638334 & 0.955880946339725 & 0.983451402259195 \tabularnewline
logtg & 0.880756436094418 & 0.8810885944584 & 0.0277777317291189 & 0.837741446817982 & 0.918791075124928 \tabularnewline
logSWS & 0.891947575341777 & 0.889541362503736 & 0.0364344739797181 & 0.826267554832962 & 0.932670599868892 \tabularnewline
logPS & 0.87291369016888 & 0.872070364167138 & 0.0508496457296118 & 0.775724271361718 & 0.927285650635181 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110785&T=12

[TABLE]
[ROW][C]BOOTSTRAP VALIDATION - LOADINGS[/C][/ROW]
[ROW][C][/C][C]Original[/C][C]Mean.Boot[/C][C]Std.Error[/C][C]perc.05[/C][C]perc.95[/C][/ROW]
[ROW][C]logP[/C][C]0.867637144235964[/C][C]0.859818792721442[/C][C]0.0686421329199473[/C][C]0.757151341090742[/C][C]0.93396984348992[/C][/ROW]
[ROW][C]logS[/C][C]0.90148243160283[/C][C]0.908250845896857[/C][C]0.0275775829472729[/C][C]0.866873235324142[/C][C]0.955396507197371[/C][/ROW]
[ROW][C]logD[/C][C]0.939748063343516[/C][C]0.930432999415067[/C][C]0.0421729871938867[/C][C]0.850186126043246[/C][C]0.975845241164157[/C][/ROW]
[ROW][C]logL[/C][C]0.838196412672888[/C][C]0.821442344494607[/C][C]0.0909881270674692[/C][C]0.644424208595763[/C][C]0.929451769448314[/C][/ROW]
[ROW][C]logWb[/C][C]0.926642148966324[/C][C]0.928637838888554[/C][C]0.0268411017900529[/C][C]0.87712941777375[/C][C]0.961680675047155[/C][/ROW]
[ROW][C]logWbr[/C][C]0.969982738285346[/C][C]0.96974957074225[/C][C]0.00959795870638334[/C][C]0.955880946339725[/C][C]0.983451402259195[/C][/ROW]
[ROW][C]logtg[/C][C]0.880756436094418[/C][C]0.8810885944584[/C][C]0.0277777317291189[/C][C]0.837741446817982[/C][C]0.918791075124928[/C][/ROW]
[ROW][C]logSWS[/C][C]0.891947575341777[/C][C]0.889541362503736[/C][C]0.0364344739797181[/C][C]0.826267554832962[/C][C]0.932670599868892[/C][/ROW]
[ROW][C]logPS[/C][C]0.87291369016888[/C][C]0.872070364167138[/C][C]0.0508496457296118[/C][C]0.775724271361718[/C][C]0.927285650635181[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110785&T=12

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110785&T=12

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

BOOTSTRAP VALIDATION - LOADINGS
	Original	Mean.Boot	Std.Error	perc.05	perc.95
logP	0.867637144235964	0.859818792721442	0.0686421329199473	0.757151341090742	0.93396984348992
logS	0.90148243160283	0.908250845896857	0.0275775829472729	0.866873235324142	0.955396507197371
logD	0.939748063343516	0.930432999415067	0.0421729871938867	0.850186126043246	0.975845241164157
logL	0.838196412672888	0.821442344494607	0.0909881270674692	0.644424208595763	0.929451769448314
logWb	0.926642148966324	0.928637838888554	0.0268411017900529	0.87712941777375	0.961680675047155
logWbr	0.969982738285346	0.96974957074225	0.00959795870638334	0.955880946339725	0.983451402259195
logtg	0.880756436094418	0.8810885944584	0.0277777317291189	0.837741446817982	0.918791075124928
logSWS	0.891947575341777	0.889541362503736	0.0364344739797181	0.826267554832962	0.932670599868892
logPS	0.87291369016888	0.872070364167138	0.0508496457296118	0.775724271361718	0.927285650635181

BOOTSTRAP VALIDATION - PATHS
	Original	Mean.Boot	Std.Error	perc.05	perc.95
S1->S2	0.47183687754145	0.483562230062537	0.107995248448403	0.273084624150484	0.647936628327493
S1->S3	-0.462761043658846	-0.45777883072231	0.0859675850984513	-0.596118087159433	-0.304830600724995
S2->S3	-0.476656648167647	-0.47865412360967	0.0737036525665237	-0.583769221183514	-0.326713250725817

\begin{tabular}{lllllllll}
\hline
BOOTSTRAP VALIDATION - PATHS \tabularnewline
 & Original & Mean.Boot & Std.Error & perc.05 & perc.95 \tabularnewline
S1->S2 & 0.47183687754145 & 0.483562230062537 & 0.107995248448403 & 0.273084624150484 & 0.647936628327493 \tabularnewline
S1->S3 & -0.462761043658846 & -0.45777883072231 & 0.0859675850984513 & -0.596118087159433 & -0.304830600724995 \tabularnewline
S2->S3 & -0.476656648167647 & -0.47865412360967 & 0.0737036525665237 & -0.583769221183514 & -0.326713250725817 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110785&T=13

[TABLE]
[ROW][C]BOOTSTRAP VALIDATION - PATHS[/C][/ROW]
[ROW][C][/C][C]Original[/C][C]Mean.Boot[/C][C]Std.Error[/C][C]perc.05[/C][C]perc.95[/C][/ROW]
[ROW][C]S1->S2[/C][C]0.47183687754145[/C][C]0.483562230062537[/C][C]0.107995248448403[/C][C]0.273084624150484[/C][C]0.647936628327493[/C][/ROW]
[ROW][C]S1->S3[/C][C]-0.462761043658846[/C][C]-0.45777883072231[/C][C]0.0859675850984513[/C][C]-0.596118087159433[/C][C]-0.304830600724995[/C][/ROW]
[ROW][C]S2->S3[/C][C]-0.476656648167647[/C][C]-0.47865412360967[/C][C]0.0737036525665237[/C][C]-0.583769221183514[/C][C]-0.326713250725817[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110785&T=13

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110785&T=13

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

BOOTSTRAP VALIDATION - PATHS
	Original	Mean.Boot	Std.Error	perc.05	perc.95
S1->S2	0.47183687754145	0.483562230062537	0.107995248448403	0.273084624150484	0.647936628327493
S1->S3	-0.462761043658846	-0.45777883072231	0.0859675850984513	-0.596118087159433	-0.304830600724995
S2->S3	-0.476656648167647	-0.47865412360967	0.0737036525665237	-0.583769221183514	-0.326713250725817

BOOTSTRAP VALIDATION - RSQ
	Original	Mean.Boot	Std.Error	perc.05	perc.95
S2	0.222630039008065	0.245378774293612	0.101153358283062	0.0745758610019033	0.419822385220305
S3	0.649503134084065	0.65639977255227	0.0827425014824753	0.516256605091289	0.77969843522738

\begin{tabular}{lllllllll}
\hline
BOOTSTRAP VALIDATION - RSQ \tabularnewline
 & Original & Mean.Boot & Std.Error & perc.05 & perc.95 \tabularnewline
S2 & 0.222630039008065 & 0.245378774293612 & 0.101153358283062 & 0.0745758610019033 & 0.419822385220305 \tabularnewline
S3 & 0.649503134084065 & 0.65639977255227 & 0.0827425014824753 & 0.516256605091289 & 0.77969843522738 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110785&T=14

[TABLE]
[ROW][C]BOOTSTRAP VALIDATION - RSQ[/C][/ROW]
[ROW][C][/C][C]Original[/C][C]Mean.Boot[/C][C]Std.Error[/C][C]perc.05[/C][C]perc.95[/C][/ROW]
[ROW][C]S2[/C][C]0.222630039008065[/C][C]0.245378774293612[/C][C]0.101153358283062[/C][C]0.0745758610019033[/C][C]0.419822385220305[/C][/ROW]
[ROW][C]S3[/C][C]0.649503134084065[/C][C]0.65639977255227[/C][C]0.0827425014824753[/C][C]0.516256605091289[/C][C]0.77969843522738[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110785&T=14

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110785&T=14

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

BOOTSTRAP VALIDATION - RSQ
	Original	Mean.Boot	Std.Error	perc.05	perc.95
S2	0.222630039008065	0.245378774293612	0.101153358283062	0.0745758610019033	0.419822385220305
S3	0.649503134084065	0.65639977255227	0.0827425014824753	0.516256605091289	0.77969843522738

BOOTSTRAP VALIDATION - TOTAL EFFECTS
	Original	Mean.Boot	Std.Error	perc.05	perc.95
S1->S2	0.47183687754145	0.483562230062537	0.107995248448403	0.273084624150484	0.647936628327493
S1->S3	-0.687665228189642	-0.687086921716286	0.0760383948821709	-0.800942444492284	-0.555220497556662
S2->S3	-0.476656648167647	-0.47865412360967	0.0737036525665237	-0.583769221183514	-0.326713250725817

\begin{tabular}{lllllllll}
\hline
BOOTSTRAP VALIDATION - TOTAL EFFECTS \tabularnewline
 & Original & Mean.Boot & Std.Error & perc.05 & perc.95 \tabularnewline
S1->S2 & 0.47183687754145 & 0.483562230062537 & 0.107995248448403 & 0.273084624150484 & 0.647936628327493 \tabularnewline
S1->S3 & -0.687665228189642 & -0.687086921716286 & 0.0760383948821709 & -0.800942444492284 & -0.555220497556662 \tabularnewline
S2->S3 & -0.476656648167647 & -0.47865412360967 & 0.0737036525665237 & -0.583769221183514 & -0.326713250725817 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110785&T=15

[TABLE]
[ROW][C]BOOTSTRAP VALIDATION - TOTAL EFFECTS[/C][/ROW]
[ROW][C][/C][C]Original[/C][C]Mean.Boot[/C][C]Std.Error[/C][C]perc.05[/C][C]perc.95[/C][/ROW]
[ROW][C]S1->S2[/C][C]0.47183687754145[/C][C]0.483562230062537[/C][C]0.107995248448403[/C][C]0.273084624150484[/C][C]0.647936628327493[/C][/ROW]
[ROW][C]S1->S3[/C][C]-0.687665228189642[/C][C]-0.687086921716286[/C][C]0.0760383948821709[/C][C]-0.800942444492284[/C][C]-0.555220497556662[/C][/ROW]
[ROW][C]S2->S3[/C][C]-0.476656648167647[/C][C]-0.47865412360967[/C][C]0.0737036525665237[/C][C]-0.583769221183514[/C][C]-0.326713250725817[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110785&T=15

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110785&T=15

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

BOOTSTRAP VALIDATION - TOTAL EFFECTS
	Original	Mean.Boot	Std.Error	perc.05	perc.95
S1->S2	0.47183687754145	0.483562230062537	0.107995248448403	0.273084624150484	0.647936628327493
S1->S3	-0.687665228189642	-0.687086921716286	0.0760383948821709	-0.800942444492284	-0.555220497556662
S2->S3	-0.476656648167647	-0.47865412360967	0.0737036525665237	-0.583769221183514	-0.326713250725817

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = ecol const sleep ; par2 = A A A ; par3 = 5 6 7 ; par4 = 1 2 3 4 ; par5 = 8 9 ; par11 = 0 0 0 ; par12 = 1 0 0 ; par13 = 1 1 0 ;

Parameters (R input):

par1 = ecol const sleep ; par2 = A A A ; par3 = 5 6 7 ; par4 = 1 2 3 4 ; par5 = 8 9 ; par6 = ; par7 = ; par8 = ; par9 = ; par10 = ; par11 = 0 0 0 ; par12 = 1 0 0 ; par13 = 1 1 0 ; par14 = ; par15 = ; par16 = ; par17 = ; par18 = ;

R code (references can be found in the software module):

library(plspm)
library(diagram)
y <- as.data.frame(t(y))
is.data.frame(y)
head(y)
trim <-	function(char) {
return(sub('s+$', '', sub('^s+', '', char)))
}
(latnames <- strsplit(par1,' ')[[1]])
(n <- length(latnames))
(L1 <- as.numeric(strsplit(par3,' ')[[1]]))
(L2 <- as.numeric(strsplit(par4,' ')[[1]]))
(L3 <- as.numeric(strsplit(par5,' ')[[1]]))
(L4 <- as.numeric(strsplit(par6,' ')[[1]]))
(L5 <- as.numeric(strsplit(par7,' ')[[1]]))
(L6 <- as.numeric(strsplit(par8,' ')[[1]]))
(L7 <- as.numeric(strsplit(par9,' ')[[1]]))
(L8 <- as.numeric(strsplit(par10,' ')[[1]]))
(S1 <- as.numeric(strsplit(par11,' ')[[1]]))
(S2 <- as.numeric(strsplit(par12,' ')[[1]]))
(S3 <- as.numeric(strsplit(par13,' ')[[1]]))
(S4 <- as.numeric(strsplit(par14,' ')[[1]]))
(S5 <- as.numeric(strsplit(par15,' ')[[1]]))
(S6 <- as.numeric(strsplit(par16,' ')[[1]]))
(S7 <- as.numeric(strsplit(par17,' ')[[1]]))
(S8 <- as.numeric(strsplit(par18,' ')[[1]]))
if (n==1) sat.mat <- rbind(S1)
if (n==2) sat.mat <- rbind(S1,S2)
if (n==3) sat.mat <- rbind(S1,S2,S3)
if (n==4) sat.mat <- rbind(S1,S2,S3,S4)
if (n==5) sat.mat <- rbind(S1,S2,S3,S4,S5)
if (n==6) sat.mat <- rbind(S1,S2,S3,S4,S5,S6)
if (n==7) sat.mat <- rbind(S1,S2,S3,S4,S5,S6,S7)
if (n==8) sat.mat <- rbind(S1,S2,S3,S4,S5,S6,S7,S8)
sat.mat
if (n==1) sat.sets <- list(L1)
if (n==2) sat.sets <- list(L1,L2)
if (n==3) sat.sets <- list(L1,L2,L3)
if (n==4) sat.sets <- list(L1,L2,L3,L4)
if (n==5) sat.sets <- list(L1,L2,L3,L4,L5)
if (n==6) sat.sets <- list(L1,L2,L3,L4,L5,L6)
if (n==7) sat.sets <- list(L1,L2,L3,L4,L5,L6,L7)
if (n==8) sat.sets <- list(L1,L2,L3,L4,L5,L6,L7,L8)
sat.sets
(sat.mod <- strsplit(par2,' ')[[1]])
res <- plspm(x=y, sat.mat, sat.sets, sat.mod, scheme='centroid', scaled=TRUE, boot.val=TRUE)
(r <- summary(res))
myr <- res$path.coefs
myind <- 1
for (j in 1:(length(sat.mat[1,])-1)) {
for (i in 1:length(sat.mat[,1])) {
if (sat.mat[i,j] == 1) {
if ((res$boot$path[myind,'perc.05'] < 0) && (res$boot$path[myind,'perc.95'] > 0)) {
myr[i,j] = 0
}
myind = myind + 1
}
}
}
bitmap(file='test1.png')
plotmat(round(myr,4), pos = NULL, curve = 0, name = latnames,
lwd = 1, box.lwd = 1, cex.txt = 1, box.type = 'circle',
box.prop = 0.5, box.cex = 1, arr.type = 'triangle',
arr.pos = 0.5, shadow.size = 0.01, prefix = '', arr.lcol = 'blue',
arr.col = 'blue', arr.width = 0.2, main = c('Inner Model',
'Path Coefficients'))
dev.off()
myr <- res$path.coefs
myind <- 1
myi <- 1
for (j in 1:(length(sat.mat[1,])-1)) {
for (i in 1:length(sat.mat[,1])) {
if (i > j) {
myr[i,j] = res$boot$total.efs[myi,'Original']
myi = myi + 1
if ((res$boot$total.efs[myind,'perc.05'] < 0) && (res$boot$total.efs[myind,'perc.95'] > 0)) {
myr[i,j] = 0
}
myind = myind + 1
}
}
}
bitmap(file='test2.png')
plotmat(round(myr,4), pos = NULL, curve = 0, name = latnames,
lwd = 1, box.lwd = 1, cex.txt = 1, box.type = 'circle',
box.prop = 0.5, box.cex = 1, arr.type = 'triangle',
arr.pos = 0.5, shadow.size = 0.01, prefix = '', arr.lcol = 'blue',
arr.col = 'blue', arr.width = 0.2, main = c('Inner Model',
'Total Effects'))
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'PARTIAL LEAST SQUARES PATH MODELING (PLS-PM)',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'MODEL SPECIFICATION',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Number of Cases',header=TRUE)
a<-table.element(a,r$xxx$obs)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Latent Variables',header=TRUE)
a<-table.element(a,n)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Manifest Variables',header=TRUE)
a<-table.element(a,length(y[1,]))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Scaled?',header=TRUE)
a<-table.element(a,r$xxx$scaled)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Weighting Scheme',header=TRUE)
a<-table.element(a,r$xx$scheme)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Bootstrapping?',header=TRUE)
a<-table.element(a,r$xx$boot.val)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Bootstrap samples',header=TRUE)
a<-table.element(a,r$xx$br)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'BLOCKS DEFINITION',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Block',header=TRUE)
a<-table.element(a,'Type',header=TRUE)
a<-table.element(a,'NMVs',header=TRUE)
a<-table.element(a,'Mode',header=TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,latnames[i],header=TRUE)
a<-table.element(a,r$input$Type[i])
a<-table.element(a,r$unidim$MVs[i])
a<-table.element(a,r$unidim$Type.measure[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'BLOCKS UNIDIMENSIONALITY',7,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Block',header=TRUE)
a<-table.element(a,'Type.measure',header=TRUE)
a<-table.element(a,'MVs',header=TRUE)
a<-table.element(a,'eig.1st',header=TRUE)
a<-table.element(a,'eig.2nd',header=TRUE)
a<-table.element(a,'C.alpha',header=TRUE)
a<-table.element(a,'DG.rho',header=TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,latnames[i],header=TRUE)
a<-table.element(a,r$unidim$Type.measure[i])
a<-table.element(a,r$unidim$MVs[i])
a<-table.element(a,r$unidim$eig.1st[i])
a<-table.element(a,r$unidim$eig.2nd[i])
a<-table.element(a,r$unidim$C.alpha[i])
a<-table.element(a,r$unidim$DG.rho[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable3.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'OUTER MODEL',5,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Block',header=TRUE)
a<-table.element(a,'weights',header=TRUE)
a<-table.element(a,'std.loads',header=TRUE)
a<-table.element(a,'communal',header=TRUE)
a<-table.element(a,'redundan',header=TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,latnames[i],5,header=TRUE)
a<-table.row.end(a)
for (j in 1:length(r$outer.mod[[i]][,1])) {
a<-table.row.start(a)
a<-table.element(a,rownames(r$outer.mod[[i]])[j],header=T)
a<-table.element(a,r$outer.mod[[i]][j,1])
a<-table.element(a,r$outer.mod[[i]][j,2])
a<-table.element(a,r$outer.mod[[i]][j,3])
a<-table.element(a,r$outer.mod[[i]][j,4])
a<-table.row.end(a)
}
}
a<-table.end(a)
table.save(a,file='mytable4.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'CORRELATIONS BETWEEN MVs AND LVs',n+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Block',header=TRUE)
for (iii in 1:n) {
a<-table.element(a,latnames[iii],header=TRUE)
}
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,latnames[i],n+1,header=TRUE)
a<-table.row.end(a)
for (j in 1:length(r$outer.cor[[i]][,1])) {
a<-table.row.start(a)
a<-table.element(a,rownames(r$outer.cor[[i]])[j],header=T)
for (iii in 1:n) {
a<-table.element(a,r$outer.cor[[i]][j,iii])
}
a<-table.row.end(a)
}
}
a<-table.end(a)
table.save(a,file='mytable5.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'INNER MODEL',3,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Block',header=TRUE)
a<-table.element(a,'Concept',header=TRUE)
a<-table.element(a,'Value',header=TRUE)
a<-table.row.end(a)
for (i in 1:(length(labels(r$inner.mod)))) {
a<-table.row.start(a)
print (paste('i=',i,sep=''))
a<-table.element(a,labels(r$inner.mod)[i],3,header=TRUE)
a<-table.row.end(a)
for (j in 1:length(r$inner.mod[[i]][,1])) {
print (paste('j=',j,sep=''))
a<-table.row.start(a)
a<-table.element(a,rownames(r$inner.mod[[i]])[j],header=T)
a<-table.element(a,r$inner.mod[[i]][j,1],header=T)
a<-table.element(a,r$inner.mod[[i]][j,2])
a<-table.row.end(a)
}
}
a<-table.end(a)
table.save(a,file='mytable6.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'CORRELATIONS BETWEEN LVs',n+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'',header=TRUE)
for (iii in 1:n) {
a<-table.element(a,latnames[iii],header=TRUE)
}
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,latnames[i],header=T)
for (j in 1:n) {
a<-table.element(a,r$latent.cor[i,j])
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable7.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'SUMMARY INNER MODEL',8,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'',header=TRUE)
a<-table.element(a,'LV.Type',header=TRUE)
a<-table.element(a,'Measure',header=TRUE)
a<-table.element(a,'MVs',header=TRUE)
a<-table.element(a,'R.square',header=TRUE)
a<-table.element(a,'Av.Commu',header=TRUE)
a<-table.element(a,'Av.Redun',header=TRUE)
a<-table.element(a,'AVE',header=TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,latnames[i],header=T)
a<-table.element(a,r$inner.sum[i,1])
a<-table.element(a,r$inner.sum[i,2])
a<-table.element(a,r$inner.sum[i,3])
a<-table.element(a,r$inner.sum[i,4])
a<-table.element(a,r$inner.sum[i,5])
a<-table.element(a,r$inner.sum[i,6])
a<-table.element(a,r$inner.sum[i,7])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable8.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'GOODNESS-OF-FIT',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'GoF',header=TRUE)
a<-table.element(a,'Value',header=TRUE)
a<-table.row.end(a)
for (i in 1:4) {
a<-table.row.start(a)
a<-table.element(a,r$gof[i,1],header=T)
a<-table.element(a,r$gof[i,2])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable9.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'TOTAL EFFECTS',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'relationships',header=TRUE)
a<-table.element(a,'dir.effect',header=TRUE)
a<-table.element(a,'ind.effect',header=TRUE)
a<-table.element(a,'tot.effect',header=TRUE)
a<-table.row.end(a)
for (i in 1:length(r$effects[,1])) {
a<-table.row.start(a)
a<-table.element(a,r$effects[i,1],header=T)
a<-table.element(a,r$effects[i,2])
a<-table.element(a,r$effects[i,3])
a<-table.element(a,r$effects[i,4])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable10.tab')
dum <- r$boot$weights
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'BOOTSTRAP VALIDATION - WEIGHTS',length(colnames(dum))+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'',header=TRUE)
for (i in 1:length(colnames(dum))) {
a<-table.element(a,colnames(dum)[i],header=TRUE)
}
a<-table.row.end(a)
for (i in 1:length(rownames(dum))) {
a<-table.row.start(a)
a<-table.element(a,rownames(dum)[i],header=T)
for (j in 1:length(colnames(dum))) {
a<-table.element(a,dum[i,j])
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable11.tab')
dum <- r$boot$loadings
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'BOOTSTRAP VALIDATION - LOADINGS',length(colnames(dum))+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'',header=TRUE)
for (i in 1:length(colnames(dum))) {
a<-table.element(a,colnames(dum)[i],header=TRUE)
}
a<-table.row.end(a)
for (i in 1:length(rownames(dum))) {
a<-table.row.start(a)
a<-table.element(a,rownames(dum)[i],header=T)
for (j in 1:length(colnames(dum))) {
a<-table.element(a,dum[i,j])
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable12.tab')
dum <- r$boot$paths
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'BOOTSTRAP VALIDATION - PATHS',length(colnames(dum))+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'',header=TRUE)
for (i in 1:length(colnames(dum))) {
a<-table.element(a,colnames(dum)[i],header=TRUE)
}
a<-table.row.end(a)
for (i in 1:length(rownames(dum))) {
a<-table.row.start(a)
a<-table.element(a,rownames(dum)[i],header=T)
for (j in 1:length(colnames(dum))) {
a<-table.element(a,dum[i,j])
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable13.tab')
dum <- r$boot$rsq
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'BOOTSTRAP VALIDATION - RSQ',length(colnames(dum))+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'',header=TRUE)
for (i in 1:length(colnames(dum))) {
a<-table.element(a,colnames(dum)[i],header=TRUE)
}
a<-table.row.end(a)
for (i in 1:length(rownames(dum))) {
a<-table.row.start(a)
a<-table.element(a,rownames(dum)[i],header=T)
for (j in 1:length(colnames(dum))) {
a<-table.element(a,dum[i,j])
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable14.tab')
dum <- r$boot$total.efs
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'BOOTSTRAP VALIDATION - TOTAL EFFECTS',length(colnames(dum))+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'',header=TRUE)
for (i in 1:length(colnames(dum))) {
a<-table.element(a,colnames(dum)[i],header=TRUE)
}
a<-table.row.end(a)
for (i in 1:length(rownames(dum))) {
a<-table.row.start(a)
a<-table.element(a,rownames(dum)[i],header=T)
for (j in 1:length(colnames(dum))) {
a<-table.element(a,dum[i,j])
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable15.tab')
-SERVER-193.190.124.10:1001

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code