I have two lots of samples: one is the control lot and the other undergoes some treatment. I did three measurements for the samples: one at the initial time (T1) and the other two later.
Descriptive Statistics Lot Mean Std. Deviation NT1 1.00 124.3043 3.21127 23 2.00 124.1333 1.94286 30 Total 124.2075 2.54467 53T2 1.00 112.8261 5.81262 23 2.00 107.7000 7.42387 30 Total 109.9245 7.18398 53T3 1.00 90.3478 8.47783 23 2.00 114.7000 4.43458 30 Total 104.1321 13.77852 53The plotted data look like this:
What I did:
Use IBM SPSS (ver 20) and run General Linear Model/Repeated Measures. Established the factor to MeasureTime with three levels and the measurement. Between subjects factor was set to the lot number (1 or 2), Model full factorial, Contrasts to MeasureTime, Simple, Reference category set to first.
SPSS output a lot of statistics. Almost all are relevant (sig < 0.000) except Mauchly's Test of Sphericity.
What I want to know:
- How can I see if the mean differences in T1/T2/T3 are significant? (I expect that T1 is not andT3 is.)
- What statistic (from SPSS output) tells me that the treatment works?
I think that ANOVA would work for a factor with multiple levels, but as I read on other questions, in case of repeated measurements, ANOVA assumptions fail. The data are not independent.