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Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_Mixed Model ANOVA.wasp

Title produced by software

Mixed Within-Between Two-Way ANOVA

Date of computation

Thu, 31 May 2012 07:19:02 -0400

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/2012/May/31/t1338463165mh0651aelml6s6c.htm/, Retrieved Mon, 06 May 2024 19:13:19 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=168058, Retrieved Mon, 06 May 2024 19:13:19 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

138

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

-       [Mixed Within-Between Two-Way ANOVA] [] [2012-05-31 11:19:02] [10859d22281cca92ea91c7e9bff5476e] [Current]

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Dataseries X:

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Histogram

Boxplots

sexweightheightrepwt repht
M	77	182	77	180
F	58	161	51	159
F	53	161	54	158
M	68	177	70	175
F	59	157	59	155
M	76	170	76	165
M	76	167	77	165
M	69	186	73	180
M	71	178	71	175
M	65	171	64	170
M	70	175	75	174
F	166	57	56	163
F	51	161	52	158
F	64	168	64	165
F	52	163	57	160
F	65	166	66	165
M	92	187	101	185
F	62	168	62	165
M	76	197	75	200
F	61	175	61	171
M	119	180	124	178
F	61	170	61	170
M	65	175	66	173
M	66	173	70	170
F	54	171	59	168
F	50	166	50	165
F	63	169	61	168
F	58	166	60	160
F	39	157	41	153
M	101	183	100	180
F	71	166	71	165
M	75	178	73	175
M	79	173	76	173
F	52	164	52	161
F	68	169	63	170
M	64	176	65	175
F	56	166	54	165
M	69	174	69	171
M	88	178	86	175
M	65	187	67	188
F	54	164	53	160
M	80	178	80	178
F	63	163	59	159
M	78	183	80	180
M	85	179	82	175
F	54	160	55	158
F	54	174	56	173
F	75	162	75	158
M	82	182	85	183
F	56	165	57	163
M	74	169	73	170
M	102	185	107	185
M	65	176	64	172
M	73	183	74	180
M	75	172	70	169
M	57	173	58	170
M	68	165	69	165
M	71	177	71	170
M	71	180	76	175
F	78	173	75	169
M	97	189	98	185
F	60	162	59	160
F	64	165	63	163
F	64	164	62	161
F	52	158	51	155
M	80	178	76	175
F	62	175	61	171
M	66	173	66	175
F	55	165	54	163
F	56	163	57	159
F	50	166	50	161
F	50	160	55	150
F	63	160	64	158
M	69	182	70	180
M	69	183	70	183
F	61	165	60	163
M	55	168	56	170
F	53	169	52	175
F	60	167	55	163
F	56	170	56	170
M	59	182	61	183
M	62	178	66	175
F	53	165	53	165
F	57	163	59	160
F	57	162	56	160
M	70	173	68	170
F	56	161	56	161
M	84	184	86	183
M	69	180	71	180
M	88	189	87	185
F	56	165	57	160
M	103	185	101	182
F	50	169	50	165
F	52	159	52	153
F	55	164	55	163
M	63	178	63	175
F	47	163	47	160
F	45	163	45	160
F	62	175	63	173
F	53	164	51	160
F	52	152	51	150
F	57	167	55	164
F	64	166	64	165
F	59	166	55	163
M	84	183	90	183
M	79	179	79	171
F	55	174	57	171
M	67	179	67	179
F	76	167	77	165
F	62	168	62	163
M	83	184	83	181
M	96	184	94	183
M	75	169	76	165
M	65	178	66	178
M	78	178	77	175
M	69	167	73	165
F	68	178	68	175
F	55	165	55	163
F	45	157	45	153
F	68	171	68	169
F	44	157	44	155
F	62	166	61	163
M	87	185	89	185
F	56	160	53	158
F	50	148	47	148
M	83	177	84	175
F	53	162	53	160
F	64	172	62	168
M	90	188	91	185
M	85	191	83	188
M	66	175	68	175
F	52	163	53	160
F	53	165	55	163
F	54	176	55	176
F	64	171	66	171
F	55	160	55	155
F	55	165	55	165
F	59	157	55	158
F	70	173	67	170
M	88	184	86	183
F	57	168	58	165
F	47	162	47	160
F	47	150	45	152
F	48	163	44	160
M	54	169	58	165
M	69	172	68	174
F	57	167	56	165
F	51	163	50	160
F	54	161	54	160
F	53	162	52	158
F	59	172	58	171
M	56	163	58	161
F	59	159	59	155
F	63	170	62	168
F	66	166	66	165
M	96	191	95	188
F	53	158	50	155
M	76	169	75	165
M	61	170	61	170
M	62	168	64	168
M	71	178	68	178
M	66	170	67	165
M	81	178	82	175
M	68	174	68	173
M	80	176	78	175
F	63	165	59	160
M	70	173	70	173
F	56	162	56	160
F	60	172	55	168
F	58	169	54	166
M	76	183	75	180
F	50	158	49	155
M	88	185	93	188
M	89	173	86	173
F	59	164	59	165
F	51	156	51	158
F	62	164	61	161
M	74	175	71	175
M	83	180	80	180
M	90	181	91	178
M	79	177	81	178

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	vre.aston.ac.uk @ vre.aston.ac.uk
R Framework error message	Warning: there are blank lines in the 'Data X' field. Please, use NA for missing data - blank lines are simply deleted and are NOT treated as missing values.
R Engine error message	Error in as.vector(data) : object 'sexweightheightrepwt' not found Calls: array -> as.vector Execution halted

\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 & 2 seconds \tabularnewline
R Server & vre.aston.ac.uk @ vre.aston.ac.uk \tabularnewline
R Framework error message & Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values. \tabularnewline
R Engine error message & Error in as.vector(data) : object 'sexweightheightrepwt' not found
Calls: array -> as.vector
Execution halted
 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=168058&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]vre.aston.ac.uk @ vre.aston.ac.uk[/C][/ROW]
[ROW][C]R Framework error message[/C][C]Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.[/C][/ROW]
[ROW][C]R Engine error message[/C][C]Error in as.vector(data) : object 'sexweightheightrepwt' not found
Calls: array -> as.vector
Execution halted
[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=168058&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=168058&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	2 seconds
R Server	vre.aston.ac.uk @ vre.aston.ac.uk
R Framework error message	Warning: there are blank lines in the 'Data X' field. Please, use NA for missing data - blank lines are simply deleted and are NOT treated as missing values.
R Engine error message	Error in as.vector(data) : object 'sexweightheightrepwt' not found Calls: array -> as.vector Execution halted

Parameters (Session):

par1 = 5 ; par2 = 3 ; par3 = 4 ; par4 = 2 ; par5 = 1 ;

Parameters (R input):

par1 = 5 ; par2 = 3 ; par3 = 4 ; par4 = 2 ; par5 = 1 ;

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

par5 <- '1'
par4 <- '2'
par3 <- '4'
par2 <- '3'
par1 <- '5'
cat1 <- as.numeric(par1) #
cat2<- as.numeric(par2) #
cat3 <- as.numeric(par3)
cat4 <-as.numeric(par4)
cat5 <-as.numeric(par5)
x <- t(x)
x1<-as.numeric(x[,cat1])
wf1<-as.character(x[,cat2])
wf2 <- as.character(x[,cat3])
bf1 <- as.character(x[,cat4])
sid<- as.character(x[,cat5]) # author of ez changed within subjects variable name from sid to wid
xdf<-data.frame(x1,wf1, wf2, bf1, sid)
(V1<-dimnames(y)[[1]][cat1])
(V2<-dimnames(y)[[1]][cat2])
(V3 <-dimnames(y)[[1]][cat3])
(V4 <-dimnames(y)[[1]][cat4])
(V5 <-dimnames(y)[[1]][cat5])
names(xdf)<-c(V1, V2, V3, V4, V5)
library(ez)
library(Cairo)
(ezout <- ezANOVA(data=xdf, dv=.(mean_rt), wid=.(sid), within=.(cue, flanker), between=.(group) ) )
load(file='createtable')
a<-table.start()
nr <- nrow(ezout$ANOVA)
nc <- ncol(ezout$ANOVA)
a<-table.row.start(a)
a<-table.element(a,'Repeated Measures ANOVA', nc+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'effect', 1,TRUE)
a<-table.element(a,'Dfn',1,TRUE)
a<-table.element(a,'DFd', 1,TRUE)
a<-table.element(a, 'F', 1,TRUE)
a<-table.element(a,'p', 1,TRUE)
a<-table.element(a,'p<0.05', 1,TRUE)
a<-table.element(a, 'ges', 1,TRUE) # generalized eta-sq - was partial eta-sq in earlier version
a<-table.row.end(a)
for ( i in 1:nr){
a<-table.row.start(a)
a<-table.element(a,ezout$ANOVA$Effect[i], 1, TRUE)
for(j in 2:nc){
if ( j != 6) # author of ez reduced number of columns in output from 8
a<-table.element(a,round(ezout$ANOVA[[j]][i], digits=3), 1, FALSE)
else a<-table.element(a, ezout$ANOVA[[j]][i], 1, FALSE)
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
nr <- nrow(ezout$Mauchly)
nc <- ncol(ezout$Mauchly)
a<-table.row.start(a)
a<-table.element(a,'Mauchlys Test for Sphericity', nc+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'effect', 1,TRUE)
a<-table.element(a,'W',1,TRUE)
a<-table.element(a,'p', 1,TRUE)
a<-table.element(a,'p<0.05', 1,TRUE)
a<-table.row.end(a)
for ( i in 1:nr){
a<-table.row.start(a)
a<-table.element(a,ezout$Mauchly$Effect[i], 1, TRUE)
for(j in 2:nc){
if (j != 4)
a<-table.element(a,round(ezout$Mauchly[[j]][i], digits = 3), 1, FALSE)
else
a<-table.element(a,ezout$Mauchly[[j]][i], 1, FALSE)
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
nr <- nrow(ezout$Spher)
nc <- ncol(ezout$Sphe)
a<-table.row.start(a)
a<-table.element(a,'Sphericity Corrections', nc+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'effect', 1,TRUE)
a<-table.element(a,'GGe',1,TRUE)
a<-table.element(a,'p[GG]', 1,TRUE)
a<-table.element(a,'p[GG]<0.05', 1,TRUE)
a<-table.element(a,'HFe', 1,TRUE)
a<-table.element(a,'p[HF]', 1,TRUE)
a<-table.element(a,'p[HF]<0.05', 1,TRUE)
a<-table.row.end(a)
for ( i in 1:nr){
a<-table.row.start(a)
a<-table.element(a,ezout$Spher$Effect[i], 1, TRUE)
for(j in 2:nc){
if ( ! ((j == 4) | (j == 7)) )
a<-table.element(a,round(ezout$Spher[[j]][i], digits=3), 1, FALSE)
else
a<-table.element(a,ezout$Spher[[j]][i], 1, FALSE)
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
ezP.between<-ezPlot(data = xdf, dv = .(mean_rt), between = .(group), wid = .(sid), do_lines=FALSE, x_lab='group', y_lab='RT' , x=.(group))
bitmap(file = 'between.cairo')
print(ezP.between)
dev.off()
ezstats_between<-ezStats(data = xdf, dv = .(mean_rt), between =.(group),  wid = .(sid))
a<-table.start()
nr <- nrow(ezstats_between)
nc <- ncol(ezstats_between)
a<-table.row.start(a)
a<-table.element(a,'Between Effects Comparisons', nc+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
for(i in 1:nc){
a<-table.element(a, names(ezstats_between)[i], 1,TRUE)
}
a<-table.row.end(a)
for ( i in 1:nr){
a<-table.row.start(a)
a<-table.element(a,ezstats_between[[1]][i], 1, TRUE)
for(j in 2:nc){
a<-table.element(a,ezstats_between[[j]][i], 1, FALSE)
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable3.tab')
ezP.within<-ezPlot(data = xdf, dv = .(mean_rt), within = .(cue, flanker), wid = .(sid), do_lines=TRUE, x_lab='flanker', y_lab='RT' , x=.(flanker), split=.(cue), split_lab = 'cue')
bitmap(file = 'within.cairo')
print(ezP.within)
dev.off()
ezstats_within <- ezStats(data = xdf, dv = .(mean_rt), within = .(cue, flanker),  wid = .(sid))
a<-table.start()
nr <- nrow(ezstats_within)
nc <- ncol(ezstats_within)
a<-table.row.start(a)
a<-table.element(a,'Within Effects Comparisons', nc+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
for(i in 1:nc){
a<-table.element(a, names(ezstats_within)[i], 1,TRUE)
}
a<-table.row.end(a)
for ( i in 1:nr){
a<-table.row.start(a)
a<-table.element(a,ezstats_within[[1]][i], 1, TRUE)
for(j in 2:nc){
a<-table.element(a, ezstats_within[[j]][i], 1, FALSE)
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable4.tab')
-SERVER-vre.aston.ac.uk

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Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code