Reporting a one way repeated measures anova

Reporting a One-Way Repeated Measures ANOVA

Reporting the Study using APA

• Note – that the reporting format shown in this learning module is for APA. For other formats consult specific format guides.

• It is also recommended to consult the latest APA manual to compare what is described in this learning module with the most updated formats for APA

• You can report that you conducted a One-Way Repeated Measures ANOVA by using the template below.

• “A one-way repeated measures ANOVA was conducted to compare the effect of (IV)______________ on (DV)_______________ in _________________, __________________, and __________________ conditions.”

• “A one-way repeated measures ANOVA was conducted to compare the effect of (IV) time of eating on (DV) pizza slices consumed, before, during and after the season.”

Reporting Results using APA

• Just fill in the blanks by using the SPSS output

• Just fill in the blanks by using the SPSS output• “There was a significant (not a significant) effect of the IV

___________, Wilks’ Lambda = ____, F (____,____) = _____, p = _____.

• Just fill in the blanks by using the SPSS output• “There was a significant (not a significant) effect of the IV

___________, Wilks’ Lambda = ____, F (____,____) = _____, p = _____.

Multivariate Testsa

Effect Value F Hypothesis df Error df Sig.

Time_eating Pillai's Trace .977 128.030b 2.000 6.000 .000

Wilks' Lambda .023 128.030b 2.000 6.000 .000

Hotelling's Trace 42.677 128.030b 2.000 6.000 .000

Roy's Largest Root 42.677 128.030b 2.000 6.000 .000

a. Design: Intercept

Within Subjects Design: Time_eating

b. Exact statistic

• Just fill in the blanks by using the SPSS output• “There was a significant effect of time of season on eating

pizza, Wilks’ Lambda = .023, F (____,____) = _____, p = _____.”

Multivariate Testsa

Wilks' Lambda .023 128.030b 2.000 6.000 .000

b. Exact statistic

pizza, Wilks’ Lambda = .023, F (____,____) = _____, p = _____.”

Multivariate Testsa

Wilks' Lambda .023 128.030b 2.000 6.000 .000

b. Exact statistic

pizza, Wilks’ Lambda = .023, F (2,____) = _____, p = _____.”

Multivariate Testsa

Wilks' Lambda .023 128.030b 2.000 6.000 .000

b. Exact statistic

pizza, Wilks’ Lambda = .023, F (2,____) = _____, p = _____.”

Multivariate Testsa

Wilks' Lambda .023 128.030b 2.000 6.000 .000

b. Exact statistic

pizza, Wilks’ Lambda = .023, F (2, 6) = _____, p = _____.”

Multivariate Testsa

Wilks' Lambda .023 128.030b 2.000 6.000 .000

b. Exact statistic

pizza, Wilks’ Lambda = .023, F (2, 6) = _____, p = _____.”

Multivariate Testsa

Wilks' Lambda .023 128.030b 2.000 6.000 .000

b. Exact statistic

pizza, Wilks’ Lambda = .023, F (2, 6) = 128, p = _____.”

Multivariate Testsa

Wilks' Lambda .023 128.030b 2.000 6.000 .000

b. Exact statistic

pizza, Wilks’ Lambda = .023, F (2, 6) = 128, p = _____.”

Multivariate Testsa

Wilks' Lambda .023 128.030b 2.000 6.000 .000

b. Exact statistic

pizza, Wilks’ Lambda = .023, F (2, 6) = 128, p = .000.”

Multivariate Testsa

Wilks' Lambda .023 128.030b 2.000 6.000 .000

b. Exact statistic

pizza, Wilks’ Lambda = .023, F (2, 6) = 128, p = .000.”

• Once the blanks are full…you have your report:

Multivariate Testsa

Wilks' Lambda .023 128.030b 2.000 6.000 .000

b. Exact statistic

There was a significant effect of time of season on eating pizza, Wilks’ Lambda = .023, F (2, 6) = 128, p = .000.

Reporting Results using APA• Note- if there is a significant difference (which there was in

this case) you would also report the pair-wise t results which look like this:

• Three paired samples t-tests were used to make post hoc comparisons between conditions.

• Three paired samples t-tests were used to make post hoc comparisons between conditions. A first paired samples t-test indicated that there was a significant difference between the number of pizza slices eaten before (M=3.0, SD=.76) and during (M= 6.3, SD=.71) the season; t(7)= 6.62, p = .000. A third paired samples t-test indicated that there was a significant difference between the number of pizza slices eaten before (M=3.0, SD=.76) and after (M =1.4, SD=.518) the season; t(7)= 6.18, p = .000.

• Three paired samples t-tests were used to make post hoc comparisons between conditions. A first paired samples t-test indicated that there was a significant difference between the number of pizza slices eaten before (M=3.0, SD=.76) and during (M= 6.3, SD=.71) the season; t(7)= 6.62, p = .000. A second paired samples t-test indicated that there was a significant difference between the number of pizza slices eaten during (M= 6.3, SD=.71) and after (M =1.4, SD=.52) the season; t(7)= 13.91, p = .000. A third paired samples t-test indicated that there was a significant difference between the number of pizza slices eaten before (M=3.0, SD=.76) and after (M =1.4, SD=.518) the season; t(7)= 6.18, p = .000.

Reporting Results using APA• Three paired samples t-tests were used to make post hoc comparisons

between conditions. A first paired samples t-test indicated that there was a significant difference between the number of pizza slices eaten before (M=3.0, SD=.76) and during (M= 6.3, SD=.71) the season; t(7)= 6.62, p = .000. A second paired samples t-test indicated that there was a significant difference between the number of pizza slices eaten during (M= 6.3, SD=.71) and after (M =1.4, SD=.52) the season; t(7)= 13.91, p = .000. A third paired samples t-test indicated that there was a significant difference between the number of pizza slices eaten before (M=3.0, SD=.76) and after (M =1.4, SD=.518) the season; t(7)= 6.18, p = .000.

Descriptive Statistics

Mean Std. Deviation N

Before 3.00 .756 8

During 6.25 .707 8

After 1.38 .518 8

Descriptive Statistics Mean Std. Deviation N

Before 3.00 .756 8

During 6.25 .707 8

After 1.38 .518 8

Before 3.00 .756 8

During 6.25 .707 8

After 1.38 .518 8

Before 3.00 .756 8

During 6.25 .707 8

After 1.38 .518 8

Before 3.00 .756 8

During 6.25 .707 8

After 1.38 .518 8

Before 3.00 .756 8

During 6.25 .707 8

After 1.38 .518 8

Before 3.00 .756 8

During 6.25 .707 8

After 1.38 .518 8

between conditions. A first paired samples t-test indicated that there was a significant difference between the number of pizza slices eaten before (M=3.0, SD=.76) and during (M= 6.3, SD=.71) the season; t(7)= -6.62, p = .000. A second paired samples t-test indicated that there was a significant difference between the number of pizza slices eaten during (M= 6.3, SD=.71) and after (M =1.4, SD=.52) the season; t(7)= 13.91, p = .000. A third paired samples t-test indicated that there was a significant difference between the number of pizza slices eaten before (M=3.0, SD=.76) and after (M =1.4, SD=.518) the season; t(7)= 6.18, p = .000.

Paired Samples Test

Paired Differences

t df Sig. (2-tailed)Mean Std. Deviation

Std. Error

95% Confidence Interval of the

Difference

Lower Upper

Pair 1 Before - During -3.250 1.389 .491 -4.411 -2.089 -6.619 7 .000

Pair 2 During - After 4.875 .991 .350 4.046 5.704 13.913 7 .000

Pair 3 Before - After 1.625 .744 .263 1.003 2.247 6.177 7 .000

Paired Samples Test

Paired Differences

Std. Error

Difference

Lower Upper

Paired Samples Test

Paired Differences

Std. Error

Difference

Lower Upper

Paired Samples Test

Paired Differences

Std. Error

Difference

Lower Upper

Paired Samples Test

Paired Differences

Std. Error

Difference

Lower Upper

Paired Samples Test

Paired Differences

Std. Error

Difference

Lower Upper

Paired Samples Test

Paired Differences

Std. Error

Difference

Lower Upper

Paired Samples Test

Paired Differences

Std. Error

Difference

Lower Upper

Paired Samples Test

Paired Differences

Std. Error

Difference

Lower Upper

Paired Samples Test

Paired Differences

Std. Error

Difference

Lower Upper

Paired Samples Test

Paired Differences

Std. Error

Difference

Lower Upper

Reporting a one way repeated measures anova

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