Running ANOVA in loops

[Sonnen Blume]

Hi, I want to run repeated measures ANOVA on math scores and semester, but the analysis has to be done for all levels of stress (high/mid/low) and sex variables (male/female).

Please let me know if this is possible do in a loop without having to subset manually.

Thank you!

* Example generated by -dataex-. To install: ssc install dataex
clear
input byte student_id str6(income sex semester) float math_score
 1 "low"    "male"   "summer"  75.79707
 2 "low"    "male"   "winter"  78.42905
 3 "low"    "male"   "fall"    77.19025
 4 "low"    "male"   "summer"  86.13298
 5 "low"    "male"   "winter"  84.81785
 6 "low"    "male"   "fall"   72.808044
 7 "low"    "male"   "summer"  60.94741
 8 "low"    "male"   "winter"  93.07262
 9 "low"    "male"   "fall"    96.72986
10 "low"    "male"   "summer"  95.45274
11 "low"    "male"   "winter"  73.21725
12 "low"    "male"   "fall"    68.09888
13 "low"    "male"   "summer"  54.45422
14 "low"    "male"   "winter" 70.273636
15 "low"    "male"   "fall"     63.7756
16 "low"    "male"   "summer"  73.78484
17 "low"    "male"   "winter"  74.67471
18 "low"    "male"   "fall"    74.49361
19 "low"    "male"   "summer"  65.32313
20 "low"    "male"   "winter"  71.98983
21 "low"    "male"   "fall"    70.34425
22 "low"    "male"   "summer"  63.78717
23 "low"    "male"   "winter"  79.24786
24 "low"    "male"   "fall"     82.9422
25 "low"    "male"   "summer" 66.953354
26 "low"    "male"   "winter"    83.132
27 "low"    "male"   "fall"    45.36668
28 "low"    "male"   "summer"  81.48463
29 "low"    "male"   "winter"  85.73037
30 "low"    "male"   "fall"    79.11235
31 "low"    "male"   "summer"  81.41333
32 "low"    "male"   "winter"   82.6655
33 "low"    "male"   "fall"     62.9081
 1 "low"    "male"   "summer"  61.16171
 2 "low"    "male"   "winter"  55.96095
 3 "low"    "male"   "fall"    65.61567
 4 "low"    "male"   "summer"  57.84998
 5 "low"    "male"   "winter"  62.85389
 6 "low"    "male"   "fall"    86.14867
 7 "low"    "male"   "summer" 65.382805
 8 "low"    "male"   "winter"  78.90556
 9 "low"    "male"   "fall"    77.81376
10 "low"    "male"   "summer"  73.22633
11 "low"    "male"   "winter"  78.89809
12 "low"    "male"   "fall"    67.75861
13 "low"    "male"   "summer"  63.12998
14 "low"    "male"   "winter" 64.939606
15 "low"    "male"   "fall"    68.52872
16 "low"    "male"   "summer"  82.71146
17 "middle" "male"   "winter"  89.11002
18 "middle" "male"   "fall"    52.11129
19 "middle" "male"   "summer"  65.83049
20 "middle" "male"   "winter"  68.84013
21 "middle" "male"   "fall"   69.065605
22 "middle" "male"   "summer"  74.18057
23 "middle" "male"   "winter"  82.78862
24 "middle" "male"   "fall"    67.25807
25 "middle" "male"   "summer" 69.853386
26 "middle" "male"   "winter"  91.95356
27 "middle" "male"   "fall"    76.73396
28 "middle" "male"   "summer"  60.11725
29 "middle" "male"   "winter"  76.10474
30 "middle" "female" "fall"    70.36514
31 "middle" "female" "summer"  67.02353
32 "middle" "female" "winter"  59.18249
33 "middle" "female" "fall"     79.9767
 1 "middle" "female" "summer"  79.48432
 2 "middle" "female" "winter"  64.14967
 3 "middle" "female" "fall"    84.50146
 4 "middle" "female" "summer"  63.50959
 5 "middle" "female" "winter"  73.36041
 6 "middle" "female" "fall"    81.75935
 7 "middle" "female" "summer"  71.10308
 8 "middle" "female" "winter"  56.25582
 9 "middle" "female" "fall"    77.83181
10 "middle" "female" "summer"  60.94855
11 "middle" "female" "winter"  78.57565
12 "middle" "female" "fall"     83.1645
13 "middle" "female" "summer"   79.3857
14 "high"   "female" "winter"  74.47901
15 "high"   "female" "fall"    56.33062
16 "high"   "female" "summer"  66.48232
17 "high"   "female" "winter"  63.08831
18 "high"   "female" "fall"    60.62999
19 "high"   "female" "summer"  76.90691
20 "high"   "female" "winter"  69.44049
21 "high"   "female" "fall"    56.89666
22 "high"   "female" "summer"  79.77268
23 "high"   "female" "winter" 68.887505
24 "high"   "female" "fall"    71.54644
25 "high"   "female" "summer"  65.84627
26 "high"   "female" "winter"  77.20901
27 "high"   "female" "fall"    66.96027
28 "high"   "female" "summer" 67.319885
29 "high"   "female" "winter" 74.991455
30 "high"   "female" "fall"    70.49643
31 "high"   "female" "summer"  71.18354
32 "high"   "female" "winter"   56.2911
33 "high"   "female" "fall"    69.46329
end

[Clyde Schechter]

Well, it would be possible if you had a variable for stress.

On the assumption that you have such a variable but didn't think to show it, the code would be

by stress sex: repeated_measures_anova_command

[Joseph Coveney]

I want to run repeated measures ANOVA on math scores and semester, but the analysis has to be done for all levels of stress (high/mid/low) and sex variables (male/female).

Please let me know if this is possible do in a loop without having to subset manually.

You could also accomplish what you want in one fell swoop by including semester, stress level and sex in suitable interaction terms in a single regression model.

Your student ID values etc. strike me as nonsensical, by the way. You might want to go back and double check things.

[Sonnen Blume]

You could also accomplish what you want in one fell swoop by including semester, stress level and sex in suitable interaction terms in a single regression model.

Your student ID values etc. strike me as nonsensical, by the way. You might want to go back and double check things.

Yes, the data is not original; it's just a sample.

[Sonnen Blume]

Well, it would be possible if you had a variable for stress.

On the assumption that you have such a variable but didn't think to show it, the code would be

by stress sex: repeated_measures_anova_command

Thank you Clyde. This is a interesting way to look into the data!
Actually my intention is to do the analysis for each level of the demographic variables e.g. sex and stress, which means there will be five different sets of results are these two variables have five levels in total.
There are many more in the original data. That's why I was thinking it might require using the loop function.

[Joro Kolev]

Thank you Clyde. This is a interesting way to look into the data!
Actually my intention is to do the analysis for each level of the demographic variables e.g. sex and stress, which means there will be five different sets of results are these two variables have five levels in total.
There are many more in the original data. That's why I was thinking it might require using the loop function.

It will require a loop if you want to save the results in any way.

What Clyde showed you will do the analysis as you want it, but the results will flash in front of your eyes, and will disappear; or more likely go into your log file.

If you want to save or output anything in publication ready format you need a loop.