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*Unverified author*

R Software Module

rwasp_Mixed Model ANOVA.wasp

Title produced by software

Mixed Within-Between Two-Way ANOVA

Date of computation

Fri, 03 Feb 2012 10:57:12 -0500

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/Feb/03/t132828466077szndrtqv38ywn.htm/, Retrieved Thu, 31 Oct 2024 22:46:13 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=161727, Retrieved Thu, 31 Oct 2024 22:46:13 +0000

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Estimated Impact

268

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

-     [Mixed Within-Between Two-Way ANOVA] [Mixed Within-Betw...] [2012-01-30 17:15:20] [98fd0e87c3eb04e0cc2efde01dbafab6]
- R       [Mixed Within-Between Two-Way ANOVA] [x] [2012-02-03 15:57:12] [d41d8cd98f00b204e9800998ecf8427e] [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	8 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 & 8 seconds \tabularnewline
R Server & vre.aston.ac.uk @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=161727&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]vre.aston.ac.uk @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=161727&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=161727&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	vre.aston.ac.uk @ vre.aston.ac.uk

Repeated Measures ANOVA
effect	Dfn	DFd	F	p	p<0.05	ges
group	1	18	18.452	0	*	0.076
cue	3	54	516.584	0	*	0.897
group:cue	3	54	2.56	0.064		0.041
flanker	2	36	1349.671	0	*	0.927
group:flanker	2	36	8.779	0.001	*	0.076
cue:flanker	6	108	5.199	0	*	0.114
group:cue:flanker	6	108	6.372	0	*	0.137

\begin{tabular}{lllllllll}
\hline
Repeated Measures ANOVA \tabularnewline
effect & Dfn & DFd & F & p & p<0.05 & ges \tabularnewline
group & 1 & 18 & 18.452 & 0 & * & 0.076 \tabularnewline
cue & 3 & 54 & 516.584 & 0 & * & 0.897 \tabularnewline
group:cue & 3 & 54 & 2.56 & 0.064 &  & 0.041 \tabularnewline
flanker & 2 & 36 & 1349.671 & 0 & * & 0.927 \tabularnewline
group:flanker & 2 & 36 & 8.779 & 0.001 & * & 0.076 \tabularnewline
cue:flanker & 6 & 108 & 5.199 & 0 & * & 0.114 \tabularnewline
group:cue:flanker & 6 & 108 & 6.372 & 0 & * & 0.137 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=161727&T=1

[TABLE]
[ROW][C]Repeated Measures ANOVA[/C][/ROW]
[ROW][C]effect[/C][C]Dfn[/C][C]DFd[/C][C]F[/C][C]p[/C][C]p<0.05[/C][C]ges[/C][/ROW]
[ROW][C]group[/C][C]1[/C][C]18[/C][C]18.452[/C][C]0[/C][C]*[/C][C]0.076[/C][/ROW]
[ROW][C]cue[/C][C]3[/C][C]54[/C][C]516.584[/C][C]0[/C][C]*[/C][C]0.897[/C][/ROW]
[ROW][C]group:cue[/C][C]3[/C][C]54[/C][C]2.56[/C][C]0.064[/C][C][/C][C]0.041[/C][/ROW]
[ROW][C]flanker[/C][C]2[/C][C]36[/C][C]1349.671[/C][C]0[/C][C]*[/C][C]0.927[/C][/ROW]
[ROW][C]group:flanker[/C][C]2[/C][C]36[/C][C]8.779[/C][C]0.001[/C][C]*[/C][C]0.076[/C][/ROW]
[ROW][C]cue:flanker[/C][C]6[/C][C]108[/C][C]5.199[/C][C]0[/C][C]*[/C][C]0.114[/C][/ROW]
[ROW][C]group:cue:flanker[/C][C]6[/C][C]108[/C][C]6.372[/C][C]0[/C][C]*[/C][C]0.137[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=161727&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=161727&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	F	p	p<0.05	ges
group	1	18	18.452	0	*	0.076
cue	3	54	516.584	0	*	0.897
group:cue	3	54	2.56	0.064		0.041
flanker	2	36	1349.671	0	*	0.927
group:flanker	2	36	8.779	0.001	*	0.076
cue:flanker	6	108	5.199	0	*	0.114
group:cue:flanker	6	108	6.372	0	*	0.137

Mauchlys Test for Sphericity
effect	W	p	p<0.05
cue	0.782	0.535
group:cue	0.782	0.535
flanker	0.881	0.341
group:flanker	0.881	0.341
cue:flanker	0.174	0.125
group:cue:flanker	0.174	0.125

\begin{tabular}{lllllllll}
\hline
Mauchlys Test for Sphericity \tabularnewline
effect & W & p & p<0.05 \tabularnewline
cue & 0.782 & 0.535 &  \tabularnewline
group:cue & 0.782 & 0.535 &  \tabularnewline
flanker & 0.881 & 0.341 &  \tabularnewline
group:flanker & 0.881 & 0.341 &  \tabularnewline
cue:flanker & 0.174 & 0.125 &  \tabularnewline
group:cue:flanker & 0.174 & 0.125 &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=161727&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]0.782[/C][C]0.535[/C][C][/C][/ROW]
[ROW][C]group:cue[/C][C]0.782[/C][C]0.535[/C][C][/C][/ROW]
[ROW][C]flanker[/C][C]0.881[/C][C]0.341[/C][C][/C][/ROW]
[ROW][C]group:flanker[/C][C]0.881[/C][C]0.341[/C][C][/C][/ROW]
[ROW][C]cue:flanker[/C][C]0.174[/C][C]0.125[/C][C][/C][/ROW]
[ROW][C]group:cue:flanker[/C][C]0.174[/C][C]0.125[/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=161727&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=161727&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	0.782	0.535
group:cue	0.782	0.535
flanker	0.881	0.341
group:flanker	0.881	0.341
cue:flanker	0.174	0.125
group:cue:flanker	0.174	0.125

Sphericity Corrections
effect	GGe	p[GG]	p[GG]<0.05	HFe	p[HF]	p[HF]<0.05
cue	0.865	0	*	1.023	0	*
group:cue	0.865	0.074		1.023	0.064
flanker	0.894	0	*	0.986	0	*
group:flanker	0.894	0.001	*	0.986	0.001	*
cue:flanker	0.602	0.002	*	0.772	0	*
group:cue:flanker	0.602	0	*	0.772	0	*

\begin{tabular}{lllllllll}
\hline
Sphericity Corrections \tabularnewline
effect & GGe & p[GG] & p[GG]<0.05 & HFe & p[HF] & p[HF]<0.05 \tabularnewline
cue & 0.865 & 0 & * & 1.023 & 0 & * \tabularnewline
group:cue & 0.865 & 0.074 &  & 1.023 & 0.064 &  \tabularnewline
flanker & 0.894 & 0 & * & 0.986 & 0 & * \tabularnewline
group:flanker & 0.894 & 0.001 & * & 0.986 & 0.001 & * \tabularnewline
cue:flanker & 0.602 & 0.002 & * & 0.772 & 0 & * \tabularnewline
group:cue:flanker & 0.602 & 0 & * & 0.772 & 0 & * \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=161727&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]0.865[/C][C]0[/C][C]*[/C][C]1.023[/C][C]0[/C][C]*[/C][/ROW]
[ROW][C]group:cue[/C][C]0.865[/C][C]0.074[/C][C][/C][C]1.023[/C][C]0.064[/C][C][/C][/ROW]
[ROW][C]flanker[/C][C]0.894[/C][C]0[/C][C]*[/C][C]0.986[/C][C]0[/C][C]*[/C][/ROW]
[ROW][C]group:flanker[/C][C]0.894[/C][C]0.001[/C][C]*[/C][C]0.986[/C][C]0.001[/C][C]*[/C][/ROW]
[ROW][C]cue:flanker[/C][C]0.602[/C][C]0.002[/C][C]*[/C][C]0.772[/C][C]0[/C][C]*[/C][/ROW]
[ROW][C]group:cue:flanker[/C][C]0.602[/C][C]0[/C][C]*[/C][C]0.772[/C][C]0[/C][C]*[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=161727&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=161727&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	0.865	0	*	1.023	0	*
group:cue	0.865	0.074		1.023	0.064
flanker	0.894	0	*	0.986	0	*
group:flanker	0.894	0.001	*	0.986	0.001	*
cue:flanker	0.602	0.002	*	0.772	0	*
group:cue:flanker	0.602	0	*	0.772	0	*

Between Effects Comparisons
group	N	Mean	SD	FLSD
Ctrl	10	409.956666666667	3.48954302077323	2.92682865735614
Trt	10	403.9725	2.68901816149306	2.92682865735614

\begin{tabular}{lllllllll}
\hline
Between Effects Comparisons \tabularnewline
group & N & Mean & SD & FLSD \tabularnewline
Ctrl & 10 & 409.956666666667 & 3.48954302077323 & 2.92682865735614 \tabularnewline
Trt & 10 & 403.9725 & 2.68901816149306 & 2.92682865735614 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=161727&T=4

[TABLE]
[ROW][C]Between Effects Comparisons[/C][/ROW]
[ROW][C]group[/C][C]N[/C][C]Mean[/C][C]SD[/C][C]FLSD[/C][/ROW]
[ROW][C]Ctrl[/C][C]10[/C][C]409.956666666667[/C][C]3.48954302077323[/C][C]2.92682865735614[/C][/ROW]
[ROW][C]Trt[/C][C]10[/C][C]403.9725[/C][C]2.68901816149306[/C][C]2.92682865735614[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=161727&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=161727&T=4

As an alternative you can also use a QR Code:

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

Between Effects Comparisons
group	N	Mean	SD	FLSD
Ctrl	10	409.956666666667	3.48954302077323	2.92682865735614
Trt	10	403.9725	2.68901816149306	2.92682865735614

Within Effects Comparisons
cue	flanker	N	Mean	SD	FLSD
Cent	Cong	20	378.895	10.6549951221308	7.3644182056978
Cent	Inc	20	467.74	19.2827547715296	7.3644182056978
Cent	Neut	20	380.615	7.73462992004143	7.3644182056978
Double	Cong	20	375.17	14.4670260283606	7.3644182056978
Double	Inc	20	459.805	17.3126809319825	7.3644182056978
Double	Neut	20	374.535	11.2964957305119	7.3644182056978
NoCue	Cong	20	427.885	10.2240827667352	7.3644182056978
NoCue	Inc	20	497.285	11.3140004093671	7.3644182056978
NoCue	Neut	20	427.925	10.5135939570984	7.3644182056978
Spatial	Cong	20	340.83	10.3312046477497	7.3644182056978
Spatial	Inc	20	413	10.9911926463634	7.3644182056978
Spatial	Neut	20	339.89	10.8526445964494	7.3644182056978

\begin{tabular}{lllllllll}
\hline
Within Effects Comparisons \tabularnewline
cue & flanker & N & Mean & SD & FLSD \tabularnewline
Cent & Cong & 20 & 378.895 & 10.6549951221308 & 7.3644182056978 \tabularnewline
Cent & Inc & 20 & 467.74 & 19.2827547715296 & 7.3644182056978 \tabularnewline
Cent & Neut & 20 & 380.615 & 7.73462992004143 & 7.3644182056978 \tabularnewline
Double & Cong & 20 & 375.17 & 14.4670260283606 & 7.3644182056978 \tabularnewline
Double & Inc & 20 & 459.805 & 17.3126809319825 & 7.3644182056978 \tabularnewline
Double & Neut & 20 & 374.535 & 11.2964957305119 & 7.3644182056978 \tabularnewline
NoCue & Cong & 20 & 427.885 & 10.2240827667352 & 7.3644182056978 \tabularnewline
NoCue & Inc & 20 & 497.285 & 11.3140004093671 & 7.3644182056978 \tabularnewline
NoCue & Neut & 20 & 427.925 & 10.5135939570984 & 7.3644182056978 \tabularnewline
Spatial & Cong & 20 & 340.83 & 10.3312046477497 & 7.3644182056978 \tabularnewline
Spatial & Inc & 20 & 413 & 10.9911926463634 & 7.3644182056978 \tabularnewline
Spatial & Neut & 20 & 339.89 & 10.8526445964494 & 7.3644182056978 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=161727&T=5

[TABLE]
[ROW][C]Within Effects Comparisons[/C][/ROW]
[ROW][C]cue[/C][C]flanker[/C][C]N[/C][C]Mean[/C][C]SD[/C][C]FLSD[/C][/ROW]
[ROW][C]Cent[/C][C]Cong[/C][C]20[/C][C]378.895[/C][C]10.6549951221308[/C][C]7.3644182056978[/C][/ROW]
[ROW][C]Cent[/C][C]Inc[/C][C]20[/C][C]467.74[/C][C]19.2827547715296[/C][C]7.3644182056978[/C][/ROW]
[ROW][C]Cent[/C][C]Neut[/C][C]20[/C][C]380.615[/C][C]7.73462992004143[/C][C]7.3644182056978[/C][/ROW]
[ROW][C]Double[/C][C]Cong[/C][C]20[/C][C]375.17[/C][C]14.4670260283606[/C][C]7.3644182056978[/C][/ROW]
[ROW][C]Double[/C][C]Inc[/C][C]20[/C][C]459.805[/C][C]17.3126809319825[/C][C]7.3644182056978[/C][/ROW]
[ROW][C]Double[/C][C]Neut[/C][C]20[/C][C]374.535[/C][C]11.2964957305119[/C][C]7.3644182056978[/C][/ROW]
[ROW][C]NoCue[/C][C]Cong[/C][C]20[/C][C]427.885[/C][C]10.2240827667352[/C][C]7.3644182056978[/C][/ROW]
[ROW][C]NoCue[/C][C]Inc[/C][C]20[/C][C]497.285[/C][C]11.3140004093671[/C][C]7.3644182056978[/C][/ROW]
[ROW][C]NoCue[/C][C]Neut[/C][C]20[/C][C]427.925[/C][C]10.5135939570984[/C][C]7.3644182056978[/C][/ROW]
[ROW][C]Spatial[/C][C]Cong[/C][C]20[/C][C]340.83[/C][C]10.3312046477497[/C][C]7.3644182056978[/C][/ROW]
[ROW][C]Spatial[/C][C]Inc[/C][C]20[/C][C]413[/C][C]10.9911926463634[/C][C]7.3644182056978[/C][/ROW]
[ROW][C]Spatial[/C][C]Neut[/C][C]20[/C][C]339.89[/C][C]10.8526445964494[/C][C]7.3644182056978[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=161727&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=161727&T=5

As an alternative you can also use a QR Code:

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

Within Effects Comparisons
cue	flanker	N	Mean	SD	FLSD
Cent	Cong	20	378.895	10.6549951221308	7.3644182056978
Cent	Inc	20	467.74	19.2827547715296	7.3644182056978
Cent	Neut	20	380.615	7.73462992004143	7.3644182056978
Double	Cong	20	375.17	14.4670260283606	7.3644182056978
Double	Inc	20	459.805	17.3126809319825	7.3644182056978
Double	Neut	20	374.535	11.2964957305119	7.3644182056978
NoCue	Cong	20	427.885	10.2240827667352	7.3644182056978
NoCue	Inc	20	497.285	11.3140004093671	7.3644182056978
NoCue	Neut	20	427.925	10.5135939570984	7.3644182056978
Spatial	Cong	20	340.83	10.3312046477497	7.3644182056978
Spatial	Inc	20	413	10.9911926463634	7.3644182056978
Spatial	Neut	20	339.89	10.8526445964494	7.3644182056978

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

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]) # 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

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code