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This question is related to How to analyze curvilinear seasonal data

I have data like following: 

subjectID, month, vnum1, age, gender
1          1       5    10      1 
2          1       6    15      2
3          2       6    18      2
...

I have one continuous variable (called vnum1) which is showing a curvilinear relation with month of the year (lower in summer months). However, I have 2 other variables also- age and gender. I have to determine if the curvilinear relation of vnum1 with month is independent of age and gender. How can I test this. Thanks for your help.

mdewey
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rnso
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  • Age and gender will need to be predictors and then you need to test for interactions of however you are handling month with age and gender. Standard linear model stuff. In this case the data are for people who are (certainly) aging over time but (probably) constant in gender, so at least the first change needs to be considered even if it is neglected. – Nick Cox Nov 27 '14 at 12:26
  • I tried to clarify in previous question also that subjects were not tested repeatedly. Different subjects were tested over 3 years. There was no age and gender selection of subjects tested at different times. Hence any relation between age or gender with month is likely to be by chance only. – rnso Nov 27 '14 at 12:33
  • If no person is **ever** measured twice, then OK. – Nick Cox Nov 27 '14 at 12:40
  • No person was ever measured twice. – rnso Nov 28 '14 at 03:08

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