Purpose of study: To investigate whether a self-affirmation intervention can reduce Teacher stress

Study design: I used a 3x2 mixed factorial design with a 3 level, between-subjects factor (group: self-affirmation condition, control condition 1, control condition 2) and a 2 level within-subjects factor (time: Time 1 pre-intervention, Time 2, post-intervention).

So all participants received the same baseline survey at Time 1, then the experimental group completed the self-affirmation task a week later, and a week after that all participants received the same survey at Time 2.

My IV is the group condition: the experimental group wrote about an important value, control condition 1 wrote about their least important value, and control condition 2 did not have any task.

My DV'S are: Perceptions of Stressors, Perceptions of Strain, Resilience, Coping Style, Work Engagement, Affect, Rumination, Affective Commitment, and Self-esteem. I am hoping that the intervention will decrease perceptions of strain and increase resilience. There may also be an effect on the other variables, however I do not expect self-esteem to change. The following variables may be Mediators: Rumination, Affect and Coping Style.

Analysis:

I have looked at other similar studies (i.e. pre-post intervention comparisons) to see what stats I should do and I think I need to conduct a repeated measures MANOVA. Does this sound right?

Many questions have come up though from what I have read, and due to my lack of knowledge. Huge apologies for the length, and any help is very appreciated. MANOVA specific questions from Q5.

1. What do I do with missing data (unanswered items). Does it matter if it’s just the demographics questions missing?

2. Should I test for homogeneity of variance using Levine’s test? (we want non-sig Levine).

3. Were there any differences between those who dropped out (after Time 1 and/or the Intervention week) and those who completed all three surveys? E.g. were those who dropped out more ‘stressed’ at Time 1? Were there any demographic differences? Do I use an independent samples t-test for this?

4. I want to check that there are no systematic differences between the experimental group and each control group (both in terms of demographics and the pre-intervention survey responses). Do I use an independent samples t-test?

5. Should I conduct a MANOVA with all measures in? Or conduct a series of MANOVAs? (e.g. perceptions of stressors; perceptions of strain; resilience; work outcomes (affective commitment and work engagement); coping; rumination; affect; self-esteem).

6. If I run one MANOVA with all measures in, and there is a significant main effect (Group) and interaction effect (Group X Time) is my next step to then run a series of ANOVAs on each measure to identify where the change occurred?

7. I am also interested in whether some measures are acting as mediators: rumination, affect, coping style, and self-esteem. At what point do I look into this?

8. I am not sure when post hoc tests come into things (or the difference between simple and pair-wise comparisons).

9. Do I need to check Mauchley’s test for sphericity for both the MANOVA/s and ANOVA, or just the ANOVA?

10. I want to examine whether there are differences between the experimental group post-intervention and the control group post-intervention, but also whether the experimental group post-intervention is different from experimental group pre-intervention; how would I go about doing this?

11. One of the assumptions of MANOVAs is that the time intervals are equally spaced (e.g. responses are a week apart) however I cannot guarantee this as participants completed the survey at slightly different times. Would this be an issue during data analysis, or is it just a point to make in the discussion?

12. I would like to look at whether teachers high in resilience report lower levels of strain (and stressors). How do I do this?

As you can tell from my questions I really am very poor/unconfident at stats and also inexperienced. If there is anyone out there wiser who can help I would be so, so grateful!

Thank you all,

Lolly