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Author*Unverified author*
R Software ModuleIan.Hollidayrwasp_Mixed Model ANOVA.wasp
Title produced by softwareAnalysis of Variance Free Statistics Software (Calculator)
Date of computationThu, 28 Jan 2010 17:05:20 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Jan/29/t1264723562se9eis871v88d6t.htm/, Retrieved Thu, 31 Oct 2024 23:33:34 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=72733, Retrieved Thu, 31 Oct 2024 23:33:34 +0000
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IsPrivate?No (this computation is public)
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Estimated Impact306
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-     [Analysis of Variance Free Statistics Software (Calculator)] [mixed ANOVA versi...] [2010-01-25 10:27:16] [98fd0e87c3eb04e0cc2efde01dbafab6]
-         [Analysis of Variance Free Statistics Software (Calculator)] [] [2010-01-29 00:05:20] [281ef460708a2d79cddb44ff7ffbb05d] [Current]
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Dataseries X:
'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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time8 seconds
R Servervre.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=72733&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=72733&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=72733&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time8 seconds
R Servervre.aston.ac.uk @ vre.aston.ac.uk







Repeated Measures ANOVA
effectDfnDFdSSnSSdFpp<0.05pes
group1182148.6152096.03518.4520*0.506
cue354225468.8327856.298516.5840*0.966
group:cue3541117.4027856.2982.560.0640.125
flanker236330660.8424409.8871349.6710*0.987
group:flanker2362150.7734409.8878.7790.001*0.328
cue:flanker61083360.84611635.7585.1990*0.224
group:cue:flanker61084119.16111635.7586.3720*0.261

\begin{tabular}{lllllllll}
\hline
Repeated Measures ANOVA \tabularnewline
effect & Dfn & DFd & SSn & SSd & F & p & p<0.05 & pes \tabularnewline
group & 1 & 18 & 2148.615 & 2096.035 & 18.452 & 0 & * & 0.506 \tabularnewline
cue & 3 & 54 & 225468.832 & 7856.298 & 516.584 & 0 & * & 0.966 \tabularnewline
group:cue & 3 & 54 & 1117.402 & 7856.298 & 2.56 & 0.064 &  & 0.125 \tabularnewline
flanker & 2 & 36 & 330660.842 & 4409.887 & 1349.671 & 0 & * & 0.987 \tabularnewline
group:flanker & 2 & 36 & 2150.773 & 4409.887 & 8.779 & 0.001 & * & 0.328 \tabularnewline
cue:flanker & 6 & 108 & 3360.846 & 11635.758 & 5.199 & 0 & * & 0.224 \tabularnewline
group:cue:flanker & 6 & 108 & 4119.161 & 11635.758 & 6.372 & 0 & * & 0.261 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=72733&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]2148.615[/C][C]2096.035[/C][C]18.452[/C][C]0[/C][C]*[/C][C]0.506[/C][/ROW]
[ROW][C]cue[/C][C]3[/C][C]54[/C][C]225468.832[/C][C]7856.298[/C][C]516.584[/C][C]0[/C][C]*[/C][C]0.966[/C][/ROW]
[ROW][C]group:cue[/C][C]3[/C][C]54[/C][C]1117.402[/C][C]7856.298[/C][C]2.56[/C][C]0.064[/C][C][/C][C]0.125[/C][/ROW]
[ROW][C]flanker[/C][C]2[/C][C]36[/C][C]330660.842[/C][C]4409.887[/C][C]1349.671[/C][C]0[/C][C]*[/C][C]0.987[/C][/ROW]
[ROW][C]group:flanker[/C][C]2[/C][C]36[/C][C]2150.773[/C][C]4409.887[/C][C]8.779[/C][C]0.001[/C][C]*[/C][C]0.328[/C][/ROW]
[ROW][C]cue:flanker[/C][C]6[/C][C]108[/C][C]3360.846[/C][C]11635.758[/C][C]5.199[/C][C]0[/C][C]*[/C][C]0.224[/C][/ROW]
[ROW][C]group:cue:flanker[/C][C]6[/C][C]108[/C][C]4119.161[/C][C]11635.758[/C][C]6.372[/C][C]0[/C][C]*[/C][C]0.261[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=72733&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=72733&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
effectDfnDFdSSnSSdFpp<0.05pes
group1182148.6152096.03518.4520*0.506
cue354225468.8327856.298516.5840*0.966
group:cue3541117.4027856.2982.560.0640.125
flanker236330660.8424409.8871349.6710*0.987
group:flanker2362150.7734409.8878.7790.001*0.328
cue:flanker61083360.84611635.7585.1990*0.224
group:cue:flanker61084119.16111635.7586.3720*0.261







Mauchlys Test for Sphericity
effectWpp<0.05
cue0.7820.535
group:cue0.7820.535
flanker0.8810.341
group:flanker0.8810.341
cue:flanker0.1740.125
group:cue:flanker0.1740.125

\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=72733&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=72733&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=72733&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
effectWpp<0.05
cue0.7820.535
group:cue0.7820.535
flanker0.8810.341
group:flanker0.8810.341
cue:flanker0.1740.125
group:cue:flanker0.1740.125







Sphericity Corrections
effectGGep[GG]p[GG]<0.05HFep[HF]p[HF]<0.05
cue0.8650*1.0230*
group:cue0.8650.0741.0230.064
flanker0.8940*0.9860*
group:flanker0.8940.001*0.9860.001*
cue:flanker0.6020.002*0.7720*
group:cue:flanker0.6020*0.7720*

\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=72733&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=72733&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=72733&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
effectGGep[GG]p[GG]<0.05HFep[HF]p[HF]<0.05
cue0.8650*1.0230*
group:cue0.8650.0741.0230.064
flanker0.8940*0.9860*
group:flanker0.8940.001*0.9860.001*
cue:flanker0.6020.002*0.7720*
group:cue:flanker0.6020*0.7720*







Between Effects Comparisons
groupNMeanSDFLSD
Ctrl10409.9566666666673.489543020773232.92682865735614
Trt10403.97252.689018161493062.92682865735614

\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=72733&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=72733&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=72733&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
groupNMeanSDFLSD
Ctrl10409.9566666666673.489543020773232.92682865735614
Trt10403.97252.689018161493062.92682865735614







Within Effects Comparisons
cueflankerNMeanSDFLSD
CentCong20378.89510.65499512213087.3644182056978
CentInc20467.7419.28275477152967.3644182056978
CentNeut20380.6157.734629920041437.3644182056978
DoubleCong20375.1714.46702602836067.3644182056978
DoubleInc20459.80517.31268093198257.3644182056978
DoubleNeut20374.53511.29649573051197.3644182056978
NoCueCong20427.88510.22408276673527.3644182056978
NoCueInc20497.28511.31400040936717.3644182056978
NoCueNeut20427.92510.51359395709847.3644182056978
SpatialCong20340.8310.33120464774977.3644182056978
SpatialInc2041310.99119264636347.3644182056978
SpatialNeut20339.8910.85264459644947.3644182056978

\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=72733&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=72733&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=72733&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
cueflankerNMeanSDFLSD
CentCong20378.89510.65499512213087.3644182056978
CentInc20467.7419.28275477152967.3644182056978
CentNeut20380.6157.734629920041437.3644182056978
DoubleCong20375.1714.46702602836067.3644182056978
DoubleInc20459.80517.31268093198257.3644182056978
DoubleNeut20374.53511.29649573051197.3644182056978
NoCueCong20427.88510.22408276673527.3644182056978
NoCueInc20497.28511.31400040936717.3644182056978
NoCueNeut20427.92510.51359395709847.3644182056978
SpatialCong20340.8310.33120464774977.3644182056978
SpatialInc2041310.99119264636347.3644182056978
SpatialNeut20339.8910.85264459644947.3644182056978



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){
if ( j != 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), sid = .(sid), do_lines=FALSE, x_lab='group', y_lab='RT' , x=.(group))
bitmap(file = 'between.png')
print(ezP.between)
dev.off()
ezstats_between<-ezStats(data = xdf, dv = .(mean_rt), between =.(group), sid = .(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), sid = .(sid), do_lines=TRUE, x_lab='flanker', y_lab='RT' , x=.(flanker), split=.(cue), split_lab = 'cue')
bitmap(file = 'within.png')
print(ezP.within)
dev.off()
ezstats_within <- ezStats(data = xdf, dv = .(mean_rt), within = .(cue, flanker), sid = .(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')
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