I have a set of about five variables of interest (continuous and categorical), collected at four time points: baseline; six months; 12-months and 24 months. All groups got the same questions and therapy but stayed in treatment for four different time intervals (Group 1: baseline only; Group 2: baseline and six moths; Group 3: baseline, six months, 12 months; Group 4: baseline, six months, 12 months, 24 months. I am trying to find an analysis that would identify significant variations at different points in time but am hampered by the fact that people dropped out at each stage. Have run analyses with just the 24 month group but would like to compare all those who completed baseline, etc. as well. Does anyone work with data where there is no experimental condition -- all treatment the same -- but the duration changes? Would love to hear what analysis you use. Thanks.
examines the possibility of repeated measures ANOVA, but you must analyze the fulfillment of assumptions.
CJ
You can do Repeted measures in SPSS easily. Please find attached files. They can help you.
Good Luck
I can send you some other files by mail. Only leave your mail address.
Article Repeated measures analysis: ANOVA, MANOVA, and HLM
Dear Lia
I'm in agree with ANOVA two way test, with a Newman Keulls test to analize the possible significant differences.
Best regards
Emilia
I would recommend a linear mixed effects model, where the treatment is a time-varying co-variate. You can then include all data and test if the slopes are different in treatment vs no treatment.
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