## Free Statistics

of Irreproducible Research!

Author's title
Author*Unverified author*
R Software Module--
Title produced by softwareMixed Within-Between Two-Way ANOVA
Date of computationFri, 03 Feb 2012 08:29:49 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Feb/03/t1328278518vh3ov9tcjdzklxm.htm/, Retrieved Thu, 07 Jul 2022 14:17:23 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=161725, Retrieved Thu, 07 Jul 2022 14:17:23 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact161
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]
- RM      [Mixed Within-Between Two-Way ANOVA] [Anova tests for s...] [2012-02-03 13:29:49] [d41d8cd98f00b204e9800998ecf8427e] [Current]
Feedback Forum

Post a new message
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 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=161725&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=161725&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=161725&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=161725&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=161725&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=161725&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=161725&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=161725&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=161725&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=161725&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=161725&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=161725&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=161725&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=161725&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=161725&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=161725&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=161725&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=161725&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

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 widxdf<-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 versiona<-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 8a<-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$Mauchly[[j]][i], digits = 3), 1, FALSE)elsea<-table.element(a,ezout$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$Spher[[j]][i], digits=3), 1, FALSE)elsea<-table.element(a,ezout$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