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*The author of this computation has been verified*

R Software Module

Ian.Hollidayrwasp_Mixed Model ANOVA.wasp

Title produced by software

Analysis of Variance Free Statistics Software (Calculator)

Date of computation

Sun, 24 Jan 2010 13:29:50 -0700

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Jan/24/t1264365137wetdo5csk9h9h3w.htm/, Retrieved Fri, 03 May 2024 03:24:59 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=72417, Retrieved Fri, 03 May 2024 03:24:59 +0000

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No (this computation is public)

User-defined keywords

repeated measures, within subjects, ANOVA, ezANOVA

Estimated Impact

224

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-       [Analysis of Variance Free Statistics Software (Calculator)] [Repeated Measures...] [2010-01-24 20:29:50] [a9208f4f8d3b118336aae915785f2bd9] [Current]

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'1'	'Trt'	'NoCue'	'Neut'	433.5
'1'	'Trt'	'NoCue'	'Cong'	423.9
'1'	'Trt'	'NoCue'	'Inc'	490.9
'1'	'Trt'	'Cent'	'Neut'	385.2
'1'	'Trt'	'Cent'	'Cong'	368.6
'1'	'Trt'	'Cent'	'Inc'	473.4
'1'	'Trt'	'Double'	'Neut'	378.9
'1'	'Trt'	'Double'	'Cong'	378.9
'1'	'Trt'	'Double'	'Inc'	455.4
'1'	'Trt'	'Spatial'	'Neut'	328.1
'1'	'Trt'	'Spatial'	'Cong'	350.2
'1'	'Trt'	'Spatial'	'Inc'	407.2
'2'	'Trt'	'NoCue'	'Neut'	436.4
'2'	'Trt'	'NoCue'	'Cong'	441.9
'2'	'Trt'	'NoCue'	'Inc'	483.3
'2'	'Trt'	'Cent'	'Neut'	374.2
'2'	'Trt'	'Cent'	'Cong'	389.8
'2'	'Trt'	'Cent'	'Inc'	455.7
'2'	'Trt'	'Double'	'Neut'	357.0
'2'	'Trt'	'Double'	'Cong'	384.2
'2'	'Trt'	'Double'	'Inc'	433.0
'2'	'Trt'	'Spatial'	'Neut'	339.4
'2'	'Trt'	'Spatial'	'Cong'	337.6
'2'	'Trt'	'Spatial'	'Inc'	421.0
'3'	'Trt'	'NoCue'	'Neut'	428.7
'3'	'Trt'	'NoCue'	'Cong'	428.1
'3'	'Trt'	'NoCue'	'Inc'	503.3
'3'	'Trt'	'Cent'	'Neut'	371.2
'3'	'Trt'	'Cent'	'Cong'	368.0
'3'	'Trt'	'Cent'	'Inc'	436.5
'3'	'Trt'	'Double'	'Neut'	392.3
'3'	'Trt'	'Double'	'Cong'	356.3
'3'	'Trt'	'Double'	'Inc'	432.7
'3'	'Trt'	'Spatial'	'Neut'	331.3
'3'	'Trt'	'Spatial'	'Cong'	334.6
'3'	'Trt'	'Spatial'	'Inc'	431.4
'4'	'Trt'	'NoCue'	'Neut'	415.5
'4'	'Trt'	'NoCue'	'Cong'	433.3
'4'	'Trt'	'NoCue'	'Inc'	498.5
'4'	'Trt'	'Cent'	'Neut'	384.8
'4'	'Trt'	'Cent'	'Cong'	383.2
'4'	'Trt'	'Cent'	'Inc'	438.5
'4'	'Trt'	'Double'	'Neut'	370.3
'4'	'Trt'	'Double'	'Cong'	399.4
'4'	'Trt'	'Double'	'Inc'	445.9
'4'	'Trt'	'Spatial'	'Neut'	320.7
'4'	'Trt'	'Spatial'	'Cong'	342.8
'4'	'Trt'	'Spatial'	'Inc'	407.0
'5'	'Trt'	'NoCue'	'Neut'	429.1
'5'	'Trt'	'NoCue'	'Cong'	436.9
'5'	'Trt'	'NoCue'	'Inc'	499.0
'5'	'Trt'	'Cent'	'Neut'	378.1
'5'	'Trt'	'Cent'	'Cong'	394.6
'5'	'Trt'	'Cent'	'Inc'	471.4
'5'	'Trt'	'Double'	'Neut'	370.6
'5'	'Trt'	'Double'	'Cong'	370.7
'5'	'Trt'	'Double'	'Inc'	447.1
'5'	'Trt'	'Spatial'	'Neut'	332.5
'5'	'Trt'	'Spatial'	'Cong'	329.9
'5'	'Trt'	'Spatial'	'Inc'	418.3
'6'	'Trt'	'NoCue'	'Neut'	435.3
'6'	'Trt'	'NoCue'	'Cong'	422.7
'6'	'Trt'	'NoCue'	'Inc'	480.0
'6'	'Trt'	'Cent'	'Neut'	390.7
'6'	'Trt'	'Cent'	'Cong'	366.9
'6'	'Trt'	'Cent'	'Inc'	461.5
'6'	'Trt'	'Double'	'Neut'	354.1
'6'	'Trt'	'Double'	'Cong'	385.6
'6'	'Trt'	'Double'	'Inc'	435.4
'6'	'Trt'	'Spatial'	'Neut'	336.3
'6'	'Trt'	'Spatial'	'Cong'	335.0
'6'	'Trt'	'Spatial'	'Inc'	399.6
'7'	'Trt'	'NoCue'	'Neut'	435.4
'7'	'Trt'	'NoCue'	'Cong'	412.3
'7'	'Trt'	'NoCue'	'Inc'	484.9
'7'	'Trt'	'Cent'	'Neut'	387.8
'7'	'Trt'	'Cent'	'Cong'	380.5
'7'	'Trt'	'Cent'	'Inc'	443.4
'7'	'Trt'	'Double'	'Neut'	361.9
'7'	'Trt'	'Double'	'Cong'	346.4
'7'	'Trt'	'Double'	'Inc'	452.1
'7'	'Trt'	'Spatial'	'Neut'	351.1
'7'	'Trt'	'Spatial'	'Cong'	345.6
'7'	'Trt'	'Spatial'	'Inc'	424.7
'8'	'Trt'	'NoCue'	'Neut'	402.9
'8'	'Trt'	'NoCue'	'Cong'	412.7
'8'	'Trt'	'NoCue'	'Inc'	502.4
'8'	'Trt'	'Cent'	'Neut'	387.8
'8'	'Trt'	'Cent'	'Cong'	358.2
'8'	'Trt'	'Cent'	'Inc'	437.8
'8'	'Trt'	'Double'	'Neut'	357.4
'8'	'Trt'	'Double'	'Cong'	401.8
'8'	'Trt'	'Double'	'Inc'	459.5
'8'	'Trt'	'Spatial'	'Neut'	360.1
'8'	'Trt'	'Spatial'	'Cong'	335.6
'8'	'Trt'	'Spatial'	'Inc'	405.1
'9'	'Trt'	'NoCue'	'Neut'	419.2
'9'	'Trt'	'NoCue'	'Cong'	420.1
'9'	'Trt'	'NoCue'	'Inc'	500.0
'9'	'Trt'	'Cent'	'Neut'	386.1
'9'	'Trt'	'Cent'	'Cong'	381.4
'9'	'Trt'	'Cent'	'Inc'	460.0
'9'	'Trt'	'Double'	'Neut'	370.2
'9'	'Trt'	'Double'	'Cong'	369.4
'9'	'Trt'	'Double'	'Inc'	445.4
'9'	'Trt'	'Spatial'	'Neut'	351.2
'9'	'Trt'	'Spatial'	'Cong'	336.6
'9'	'Trt'	'Spatial'	'Inc'	422.3
'10'	'Trt'	'NoCue'	'Neut'	441.6
'10'	'Trt'	'NoCue'	'Cong'	432.2
'10'	'Trt'	'NoCue'	'Inc'	516.9
'10'	'Trt'	'Cent'	'Neut'	382.5
'10'	'Trt'	'Cent'	'Cong'	376.9
'10'	'Trt'	'Cent'	'Inc'	442.9
'10'	'Trt'	'Double'	'Neut'	385.6
'10'	'Trt'	'Double'	'Cong'	385.9
'10'	'Trt'	'Double'	'Inc'	457.8
'10'	'Trt'	'Spatial'	'Neut'	342.2
'10'	'Trt'	'Spatial'	'Cong'	331.5
'10'	'Trt'	'Spatial'	'Inc'	408.1
'11'	'Ctrl'	'NoCue'	'Neut'	446.7
'11'	'Ctrl'	'NoCue'	'Cong'	433.8
'11'	'Ctrl'	'NoCue'	'Inc'	517.3
'11'	'Ctrl'	'Cent'	'Neut'	380.3
'11'	'Ctrl'	'Cent'	'Cong'	371.6
'11'	'Ctrl'	'Cent'	'Inc'	493.7
'11'	'Ctrl'	'Double'	'Neut'	390.9
'11'	'Ctrl'	'Double'	'Cong'	394.2
'11'	'Ctrl'	'Double'	'Inc'	482.1
'11'	'Ctrl'	'Spatial'	'Neut'	345.2
'11'	'Ctrl'	'Spatial'	'Cong'	330.7
'11'	'Ctrl'	'Spatial'	'Inc'	391.5
'12'	'Ctrl'	'NoCue'	'Neut'	420.7
'12'	'Ctrl'	'NoCue'	'Cong'	442.7
'12'	'Ctrl'	'NoCue'	'Inc'	513.3
'12'	'Ctrl'	'Cent'	'Neut'	374.7
'12'	'Ctrl'	'Cent'	'Cong'	373.0
'12'	'Ctrl'	'Cent'	'Inc'	486.7
'12'	'Ctrl'	'Double'	'Neut'	380.0
'12'	'Ctrl'	'Double'	'Cong'	374.9
'12'	'Ctrl'	'Double'	'Inc'	495.7
'12'	'Ctrl'	'Spatial'	'Neut'	352.6
'12'	'Ctrl'	'Spatial'	'Cong'	347.6
'12'	'Ctrl'	'Spatial'	'Inc'	424.4
'13'	'Ctrl'	'NoCue'	'Neut'	422.1
'13'	'Ctrl'	'NoCue'	'Cong'	424.2
'13'	'Ctrl'	'NoCue'	'Inc'	503.6
'13'	'Ctrl'	'Cent'	'Neut'	364.8
'13'	'Ctrl'	'Cent'	'Cong'	364.3
'13'	'Ctrl'	'Cent'	'Inc'	474.6
'13'	'Ctrl'	'Double'	'Neut'	383.8
'13'	'Ctrl'	'Double'	'Cong'	363.6
'13'	'Ctrl'	'Double'	'Inc'	477.1
'13'	'Ctrl'	'Spatial'	'Neut'	338.0
'13'	'Ctrl'	'Spatial'	'Cong'	332.8
'13'	'Ctrl'	'Spatial'	'Inc'	420.3
'14'	'Ctrl'	'NoCue'	'Neut'	431.7
'14'	'Ctrl'	'NoCue'	'Cong'	436.4
'14'	'Ctrl'	'NoCue'	'Inc'	481.9
'14'	'Ctrl'	'Cent'	'Neut'	376.7
'14'	'Ctrl'	'Cent'	'Cong'	388.7
'14'	'Ctrl'	'Cent'	'Inc'	484.4
'14'	'Ctrl'	'Double'	'Neut'	383.4
'14'	'Ctrl'	'Double'	'Cong'	363.5
'14'	'Ctrl'	'Double'	'Inc'	467.4
'14'	'Ctrl'	'Spatial'	'Neut'	315.9
'14'	'Ctrl'	'Spatial'	'Cong'	354.7
'14'	'Ctrl'	'Spatial'	'Inc'	408.6
'15'	'Ctrl'	'NoCue'	'Neut'	430.9
'15'	'Ctrl'	'NoCue'	'Cong'	446.8
'15'	'Ctrl'	'NoCue'	'Inc'	505.1
'15'	'Ctrl'	'Cent'	'Neut'	372.7
'15'	'Ctrl'	'Cent'	'Cong'	382.8
'15'	'Ctrl'	'Cent'	'Inc'	483.5
'15'	'Ctrl'	'Double'	'Neut'	369.3
'15'	'Ctrl'	'Double'	'Cong'	378.1
'15'	'Ctrl'	'Double'	'Inc'	461.1
'15'	'Ctrl'	'Spatial'	'Neut'	342.6
'15'	'Ctrl'	'Spatial'	'Cong'	336.2
'15'	'Ctrl'	'Spatial'	'Inc'	421.7
'16'	'Ctrl'	'NoCue'	'Neut'	425.6
'16'	'Ctrl'	'NoCue'	'Cong'	417.5
'16'	'Ctrl'	'NoCue'	'Inc'	495.2
'16'	'Ctrl'	'Cent'	'Neut'	373.9
'16'	'Ctrl'	'Cent'	'Cong'	378.6
'16'	'Ctrl'	'Cent'	'Inc'	490.9
'16'	'Ctrl'	'Double'	'Neut'	381.9
'16'	'Ctrl'	'Double'	'Cong'	358.5
'16'	'Ctrl'	'Double'	'Inc'	464.4
'16'	'Ctrl'	'Spatial'	'Neut'	340.3
'16'	'Ctrl'	'Spatial'	'Cong'	351.1
'16'	'Ctrl'	'Spatial'	'Inc'	408.4
'17'	'Ctrl'	'NoCue'	'Neut'	421.6
'17'	'Ctrl'	'NoCue'	'Cong'	432.6
'17'	'Ctrl'	'NoCue'	'Inc'	502.8
'17'	'Ctrl'	'Cent'	'Neut'	386.0
'17'	'Ctrl'	'Cent'	'Cong'	389.3
'17'	'Ctrl'	'Cent'	'Inc'	487.0
'17'	'Ctrl'	'Double'	'Neut'	369.5
'17'	'Ctrl'	'Double'	'Cong'	368.7
'17'	'Ctrl'	'Double'	'Inc'	482.0
'17'	'Ctrl'	'Spatial'	'Neut'	350.8
'17'	'Ctrl'	'Spatial'	'Cong'	333.9
'17'	'Ctrl'	'Spatial'	'Inc'	421.7
'18'	'Ctrl'	'NoCue'	'Neut'	432.5
'18'	'Ctrl'	'NoCue'	'Cong'	413.6
'18'	'Ctrl'	'NoCue'	'Inc'	484.4
'18'	'Ctrl'	'Cent'	'Neut'	388.4
'18'	'Ctrl'	'Cent'	'Cong'	374.6
'18'	'Ctrl'	'Cent'	'Inc'	475.4
'18'	'Ctrl'	'Double'	'Neut'	380.8
'18'	'Ctrl'	'Double'	'Cong'	372.6
'18'	'Ctrl'	'Double'	'Inc'	464.2
'18'	'Ctrl'	'Spatial'	'Neut'	337.4
'18'	'Ctrl'	'Spatial'	'Cong'	338.3
'18'	'Ctrl'	'Spatial'	'Inc'	407.7
'19'	'Ctrl'	'NoCue'	'Neut'	436.6
'19'	'Ctrl'	'NoCue'	'Cong'	421.7
'19'	'Ctrl'	'NoCue'	'Inc'	494.7
'19'	'Ctrl'	'Cent'	'Neut'	393.5
'19'	'Ctrl'	'Cent'	'Cong'	393.9
'19'	'Ctrl'	'Cent'	'Inc'	482.2
'19'	'Ctrl'	'Double'	'Neut'	368.6
'19'	'Ctrl'	'Double'	'Cong'	384.2
'19'	'Ctrl'	'Double'	'Inc'	477.8
'19'	'Ctrl'	'Spatial'	'Neut'	344.0
'19'	'Ctrl'	'Spatial'	'Cong'	339.6
'19'	'Ctrl'	'Spatial'	'Inc'	392.7
'20'	'Ctrl'	'NoCue'	'Neut'	412.5
'20'	'Ctrl'	'NoCue'	'Cong'	424.3
'20'	'Ctrl'	'NoCue'	'Inc'	488.2
'20'	'Ctrl'	'Cent'	'Neut'	372.9
'20'	'Ctrl'	'Cent'	'Cong'	393.0
'20'	'Ctrl'	'Cent'	'Inc'	475.3
'20'	'Ctrl'	'Double'	'Neut'	384.2
'20'	'Ctrl'	'Double'	'Cong'	366.5
'20'	'Ctrl'	'Double'	'Inc'	460.0
'20'	'Ctrl'	'Spatial'	'Neut'	338.1
'20'	'Ctrl'	'Spatial'	'Cong'	372.3
'20'	'Ctrl'	'Spatial'	'Inc'	418.3

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	3 seconds
R Server	vre.aston.ac.uk @ vre.aston.ac.uk

\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 & 3 seconds \tabularnewline
R Server & vre.aston.ac.uk @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=72417&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]vre.aston.ac.uk @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=72417&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=72417&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	3 seconds
R Server	vre.aston.ac.uk @ vre.aston.ac.uk

Repeated Measures ANOVA
effect	Dfn	DFd	SSn	SSd	F	p	p<0.05	pes
group	1	18	2148.61504166667	2096.03475	18.4515408201129	0.000435395003277032	*	0.5061937137629
cue	3	54	225468.832458333	7856.29758333334	516.584172277249	1.00658599419469e-39	*	0.966328969443067
group:cue	3	54	1117.40245833333	7856.29758333334	2.56014287094586	0.0644479754539366		0.12451970236859
flanker	2	36	330660.841583334	4409.887	1349.6706714934	1.40358100017613e-34	*	0.986838936905516
group:flanker	2	36	2150.77308333333	4409.887	8.7788905928882	0.00078458253318518	*	0.327828763571694
cue:flanker	6	108	3360.84641666665	11635.7576666667	5.19908004558246	9.82237874324665e-05	*	0.224107164394756
group:cue:flanker	6	108	4119.16091666667	11635.7576666667	6.37215887646108	9.10429080368335e-06	*	0.261452377229306

\begin{tabular}{lllllllll}
\hline
Repeated Measures ANOVA \tabularnewline
effect & Dfn & DFd & SSn & SSd & F & p & p<0.05 & pes \tabularnewline
group & 1 & 18 & 2148.61504166667 & 2096.03475 & 18.4515408201129 & 0.000435395003277032 & * & 0.5061937137629 \tabularnewline
cue & 3 & 54 & 225468.832458333 & 7856.29758333334 & 516.584172277249 & 1.00658599419469e-39 & * & 0.966328969443067 \tabularnewline
group:cue & 3 & 54 & 1117.40245833333 & 7856.29758333334 & 2.56014287094586 & 0.0644479754539366 &  & 0.12451970236859 \tabularnewline
flanker & 2 & 36 & 330660.841583334 & 4409.887 & 1349.6706714934 & 1.40358100017613e-34 & * & 0.986838936905516 \tabularnewline
group:flanker & 2 & 36 & 2150.77308333333 & 4409.887 & 8.7788905928882 & 0.00078458253318518 & * & 0.327828763571694 \tabularnewline
cue:flanker & 6 & 108 & 3360.84641666665 & 11635.7576666667 & 5.19908004558246 & 9.82237874324665e-05 & * & 0.224107164394756 \tabularnewline
group:cue:flanker & 6 & 108 & 4119.16091666667 & 11635.7576666667 & 6.37215887646108 & 9.10429080368335e-06 & * & 0.261452377229306 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=72417&T=1

[TABLE]
[ROW][C]Repeated Measures ANOVA[/C][/ROW]
[ROW][C]effect[/C][C]Dfn[/C][C]DFd[/C][C]SSn[/C][C]SSd[/C][C]F[/C][C]p[/C][C]p<0.05[/C][C]pes[/C][/ROW]
[ROW][C]group[/C][C]1[/C][C]18[/C][C]2148.61504166667[/C][C]2096.03475[/C][C]18.4515408201129[/C][C]0.000435395003277032[/C][C]*[/C][C]0.5061937137629[/C][/ROW]
[ROW][C]cue[/C][C]3[/C][C]54[/C][C]225468.832458333[/C][C]7856.29758333334[/C][C]516.584172277249[/C][C]1.00658599419469e-39[/C][C]*[/C][C]0.966328969443067[/C][/ROW]
[ROW][C]group:cue[/C][C]3[/C][C]54[/C][C]1117.40245833333[/C][C]7856.29758333334[/C][C]2.56014287094586[/C][C]0.0644479754539366[/C][C][/C][C]0.12451970236859[/C][/ROW]
[ROW][C]flanker[/C][C]2[/C][C]36[/C][C]330660.841583334[/C][C]4409.887[/C][C]1349.6706714934[/C][C]1.40358100017613e-34[/C][C]*[/C][C]0.986838936905516[/C][/ROW]
[ROW][C]group:flanker[/C][C]2[/C][C]36[/C][C]2150.77308333333[/C][C]4409.887[/C][C]8.7788905928882[/C][C]0.00078458253318518[/C][C]*[/C][C]0.327828763571694[/C][/ROW]
[ROW][C]cue:flanker[/C][C]6[/C][C]108[/C][C]3360.84641666665[/C][C]11635.7576666667[/C][C]5.19908004558246[/C][C]9.82237874324665e-05[/C][C]*[/C][C]0.224107164394756[/C][/ROW]
[ROW][C]group:cue:flanker[/C][C]6[/C][C]108[/C][C]4119.16091666667[/C][C]11635.7576666667[/C][C]6.37215887646108[/C][C]9.10429080368335e-06[/C][C]*[/C][C]0.261452377229306[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=72417&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=72417&T=1

As an alternative you can also use a QR Code:

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

Repeated Measures ANOVA
effect	Dfn	DFd	SSn	SSd	F	p	p<0.05	pes
group	1	18	2148.61504166667	2096.03475	18.4515408201129	0.000435395003277032	*	0.5061937137629
cue	3	54	225468.832458333	7856.29758333334	516.584172277249	1.00658599419469e-39	*	0.966328969443067
group:cue	3	54	1117.40245833333	7856.29758333334	2.56014287094586	0.0644479754539366		0.12451970236859
flanker	2	36	330660.841583334	4409.887	1349.6706714934	1.40358100017613e-34	*	0.986838936905516
group:flanker	2	36	2150.77308333333	4409.887	8.7788905928882	0.00078458253318518	*	0.327828763571694
cue:flanker	6	108	3360.84641666665	11635.7576666667	5.19908004558246	9.82237874324665e-05	*	0.224107164394756
group:cue:flanker	6	108	4119.16091666667	11635.7576666667	6.37215887646108	9.10429080368335e-06	*	0.261452377229306

Mauchlys Test for Sphericity
effect	W	p	p<0.05
cue	0.782145964223619	0.534594344178278
group:cue	0.782145964223619	0.534594344178278
flanker	0.8811974700955	0.341289206652215
group:flanker	0.8811974700955	0.341289206652215
cue:flanker	0.173702172294914	0.125472179480509
group:cue:flanker	0.173702172294914	0.125472179480509

\begin{tabular}{lllllllll}
\hline
Mauchlys Test for Sphericity \tabularnewline
effect & W & p & p<0.05 \tabularnewline
cue & 0.782145964223619 & 0.534594344178278 &  \tabularnewline
group:cue & 0.782145964223619 & 0.534594344178278 &  \tabularnewline
flanker & 0.8811974700955 & 0.341289206652215 &  \tabularnewline
group:flanker & 0.8811974700955 & 0.341289206652215 &  \tabularnewline
cue:flanker & 0.173702172294914 & 0.125472179480509 &  \tabularnewline
group:cue:flanker & 0.173702172294914 & 0.125472179480509 &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=72417&T=2

[TABLE]
[ROW][C]Mauchlys Test for Sphericity[/C][/ROW]
[ROW][C]effect[/C][C]W[/C][C]p[/C][C]p<0.05[/C][/ROW]
[ROW][C]cue[/C][C]0.782145964223619[/C][C]0.534594344178278[/C][C][/C][/ROW]
[ROW][C]group:cue[/C][C]0.782145964223619[/C][C]0.534594344178278[/C][C][/C][/ROW]
[ROW][C]flanker[/C][C]0.8811974700955[/C][C]0.341289206652215[/C][C][/C][/ROW]
[ROW][C]group:flanker[/C][C]0.8811974700955[/C][C]0.341289206652215[/C][C][/C][/ROW]
[ROW][C]cue:flanker[/C][C]0.173702172294914[/C][C]0.125472179480509[/C][C][/C][/ROW]
[ROW][C]group:cue:flanker[/C][C]0.173702172294914[/C][C]0.125472179480509[/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=72417&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=72417&T=2

As an alternative you can also use a QR Code:

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

Mauchlys Test for Sphericity
effect	W	p	p<0.05
cue	0.782145964223619	0.534594344178278
group:cue	0.782145964223619	0.534594344178278
flanker	0.8811974700955	0.341289206652215
group:flanker	0.8811974700955	0.341289206652215
cue:flanker	0.173702172294914	0.125472179480509
group:cue:flanker	0.173702172294914	0.125472179480509

Sphericity Corrections
effect	GGe	p[GG]	p[GG]<0.05	HFe	p[HF]	p[HF]<0.05
cue	0.864830386647538	1.15776774018616e-34	*	1.02334241882645	1.00658599419469e-39	*
group:cue	0.864830386647538	0.0742093894260267		1.02334241882645	0.0644479754539366
flanker	0.893812780424584	3.82194475281005e-31	*	0.98581752401866	4.03569780128437e-34	*
group:flanker	0.893812780424584	0.00128994953007919	*	0.98581752401866	0.000838345933249223	*
cue:flanker	0.602194333676815	0.00153492232544425	*	0.772119773406533	0.000470280334645801	*
group:cue:flanker	0.602194333676815	0.000344679781127957	*	0.772119773406533	7.23007234995767e-05	*

\begin{tabular}{lllllllll}
\hline
Sphericity Corrections \tabularnewline
effect & GGe & p[GG] & p[GG]<0.05 & HFe & p[HF] & p[HF]<0.05 \tabularnewline
cue & 0.864830386647538 & 1.15776774018616e-34 & * & 1.02334241882645 & 1.00658599419469e-39 & * \tabularnewline
group:cue & 0.864830386647538 & 0.0742093894260267 &  & 1.02334241882645 & 0.0644479754539366 &  \tabularnewline
flanker & 0.893812780424584 & 3.82194475281005e-31 & * & 0.98581752401866 & 4.03569780128437e-34 & * \tabularnewline
group:flanker & 0.893812780424584 & 0.00128994953007919 & * & 0.98581752401866 & 0.000838345933249223 & * \tabularnewline
cue:flanker & 0.602194333676815 & 0.00153492232544425 & * & 0.772119773406533 & 0.000470280334645801 & * \tabularnewline
group:cue:flanker & 0.602194333676815 & 0.000344679781127957 & * & 0.772119773406533 & 7.23007234995767e-05 & * \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=72417&T=3

[TABLE]
[ROW][C]Sphericity Corrections[/C][/ROW]
[ROW][C]effect[/C][C]GGe[/C][C]p[GG][/C][C]p[GG]<0.05[/C][C]HFe[/C][C]p[HF][/C][C]p[HF]<0.05[/C][/ROW]
[ROW][C]cue[/C][C]0.864830386647538[/C][C]1.15776774018616e-34[/C][C]*[/C][C]1.02334241882645[/C][C]1.00658599419469e-39[/C][C]*[/C][/ROW]
[ROW][C]group:cue[/C][C]0.864830386647538[/C][C]0.0742093894260267[/C][C][/C][C]1.02334241882645[/C][C]0.0644479754539366[/C][C][/C][/ROW]
[ROW][C]flanker[/C][C]0.893812780424584[/C][C]3.82194475281005e-31[/C][C]*[/C][C]0.98581752401866[/C][C]4.03569780128437e-34[/C][C]*[/C][/ROW]
[ROW][C]group:flanker[/C][C]0.893812780424584[/C][C]0.00128994953007919[/C][C]*[/C][C]0.98581752401866[/C][C]0.000838345933249223[/C][C]*[/C][/ROW]
[ROW][C]cue:flanker[/C][C]0.602194333676815[/C][C]0.00153492232544425[/C][C]*[/C][C]0.772119773406533[/C][C]0.000470280334645801[/C][C]*[/C][/ROW]
[ROW][C]group:cue:flanker[/C][C]0.602194333676815[/C][C]0.000344679781127957[/C][C]*[/C][C]0.772119773406533[/C][C]7.23007234995767e-05[/C][C]*[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=72417&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=72417&T=3

As an alternative you can also use a QR Code:

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

Sphericity Corrections
effect	GGe	p[GG]	p[GG]<0.05	HFe	p[HF]	p[HF]<0.05
cue	0.864830386647538	1.15776774018616e-34	*	1.02334241882645	1.00658599419469e-39	*
group:cue	0.864830386647538	0.0742093894260267		1.02334241882645	0.0644479754539366
flanker	0.893812780424584	3.82194475281005e-31	*	0.98581752401866	4.03569780128437e-34	*
group:flanker	0.893812780424584	0.00128994953007919	*	0.98581752401866	0.000838345933249223	*
cue:flanker	0.602194333676815	0.00153492232544425	*	0.772119773406533	0.000470280334645801	*
group:cue:flanker	0.602194333676815	0.000344679781127957	*	0.772119773406533	7.23007234995767e-05	*

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):

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])
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)
(ezout <- ezANOVA(data=xdf, dv=.(mean_rt), sid=.(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,'SSn', 1,TRUE)
a<-table.element(a,'SSd', 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, 'pes', 1,TRUE)
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){
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$Effect[i], 1, TRUE)
for(j in 2:nc){
a<-table.element(a,ezout$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){
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')
-SERVER-vre.aston.ac.uk

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code