View source for Repeated measures ANOVA

{{TOCright}}
{{tutorial}}
{{0%done}}
==Overview==
The '''repeated measures design''' is also known as a '''within-subject design'''. In this design, participants may present scores for:
# A measure repeated over '''''time'''''<br>(e.g., [[w:Self-confidence|self-confidence]] before, after, and following-up a psycho-social intervention), and/or
# A measure repeated cross more than one '''''condition'''''<br>(e.g., experimental and control conditions), and/or
# Several related, comparable measures<br>(e.g., sub-scales of an [[IQ]] test).

Repeated-measures designs can also be understood as an extension of the '''paired-samples t-test''' (to include comparison between more than two repeated measures).

Repeated-measures designs may also be combined with between-subjects factors to create mixed-design ANOVA. Multiple repeated-measures designs can also be tested using '''MANOVAs'''.

==Why use?==
By collecting data from the same participants under repeated conditions:
* Individual differences can be reduced/eliminated as a source of between-groups differences (which helps to create a more powerful test).
* Inferential testing becomes more powerful (the sample size is not divided between conditions/groups)

==Possible designs==
# '''One-way repeated measures''' - repeated measures across one [[IV]]
# '''Two-way repeated measures''' - repeated measures across two IVs
# '''Two-way mixed split-plot design (SPANOVA)''' - repeated measures on one IV, independent groups on another IV

==Assumptions==
Most of the assumptions for between-subjects ANOVA design apply, however the key variation is  '''Sphericity''':
# Instead of the '''homogeneity of variance assumption''' (part of one-way (between-subjects) and factorial ANOVA designs), repeated-measures designs have the assumption of sphericity.
# Means that the variance of the population difference scores for any two conditions should be the same as the variance of the population difference scores for any other two conditions.
# Tested by [[w:Mauchly's sphericity test|Mauchly's sphericity test]].
# When the significance level of Mauchly’s test is < 0.05 then sphericity cannot be assumed.
# Note: the sphericity assumption is only relevant to the univariate (one-way) RM ANOVA. This assumption is commonly violated and so it is generally not recommended to use the univariate analyses – the ''p''-values tend to be inaccurate to the extent that this assumption is violated. The alternative, a multivariate test, does not require the assumption of sphericity and is therefore recommended. The multivariate test is conducted on difference scores and evaluates whether the population means for the sets of difference scores are simultaneously equal to zero.

In addition, for SPANOVA, consider '''homogeneity of intercorrelations''':
# The pattern of intercorrelations across the levels of the repeated measures factor should be consistent from level to level of the between subjects factor
# Tested using Box's ''M'' statistic.

==Exercises==
# One-way repeated measures ANOVA:
#* [http://www.pearsoned.com.au/wpsBridge/francis5/files/AQUES.sav AQUES.sav] - Francis 3.3.7, p. 66 (5th ed.)
# Two-way repeated measures
#* [http://www.pearsoned.com.au/wpsBridge/francis5/files/Repmeas.sav Repmeas.sav] - Francis 3.3.8.2, p. 76 (5th ed.)
# Mixed ANOVA
#* [http://www.pearsoned.com.au/wpsBridge/francis5/files/AQUES.sav AQUES.sav] - Francis 3.3.8.3, p. 81 (5th ed.)

==Example write-up==

==Background==
The researcher wanted to determine whether the average husband wants to express his worries to his wife more or less the longer they are married. The researcher developed the Desire to Express Worry scale (DEW) and had 30 husbands answer the questionnaire when they initially got married, and then after 5, 10, and 15 years of marriage.

==Results==
A one-way within-subjects analysis of variance (ANOVA) was conducted with the within-subjects factor being Time (four levels indicating the number of years married) and the dependent variable being the Desire to Express Worry Scale (DEW) scores. The means and standard deviations for the DEW scors are presented in Table 1. The assumptions for ANOVA were met (explain in more detail). 

The ANOVA indicated a significant time effect, Wilks’ <math>\lambda</math> = 0.62, ''F'' (3,27) = 5.57, ''p'' = .004, multivariate <math>\eta^2</math> =.38. Follow-up polynomial contrasts indicated a significant linear effect with means decreasing over time, ''F'' (1,29) = 11.56, ''p'' =.002, <math>\eta</math><math>_p^2</math> =.29. Higher-order polynomial contrasts were not significant. Men were increasingly less likely to desire to express worry to their wives with increasing years of marriage. It should be noted that there was little change in the means from 0 to 5 years, and therefore the the significant trend was due to changes after 5 years of marriage. These results suggest that men are more eager to express worry to their wives early in marriage, and that this desire decreases after 5 years of marrriage(also add a Figure and possibly pairwise, Cohen's ''d'' effect sizes).

Table 1<br>
''Means and Standard Deviations for DEW Scores''
<center>
{|
|-
! Number of years married
! ''M''
! ''SD''
|-
| 0 years
| 65.8
| 9.23
|-
| 5 years
| 65.43
| 10.69
|- 
| 10 years
| 63.1
| 10.68
|-
| 15 years
| 61.93
| 12.57
|}
</center>
Note: Skewness and kurtosis should be added to the table. Perhaps a marginal total would also be appropriate.

==See also==
* [[b:Research Methods/Mixed-model design|Mixed-model design]] (Wikibooks)
* [[w:Repeated measures design|Repeated measures design]] (Wikipedia)
* [[w:Sphericity#Sphericity in statistics|Sphericity]] (Wikipedia)

==External links==
===University of Canberra===
* [http://ucspace.canberra.edu.au/display/RMPE/Repeated+measures+ANOVA Repeated measures ANOVA] (ucspace)
** [http://ucspace.canberra.edu.au/download/attachments/45090985/RM+ANOVA+Notes.doc Repeated measures ANOVA Notes] (Handout)

===Other===
* [http://davidmlane.com/hyperstat/within-subjects.html Chapter 14 Within-Subjects ANOVA] (HyperStat Online)
{{RPME}}