Hello! I have a question about an analysis of incomplete panel data.
The data are pre and post-intervention test scores for an educational intervention, which I was planning on analyzing with repeated-measures ANOVA. The immediate pre and post scores are recorded with associated subject identifiers (n=100).
I was later sent data from a third test administered three months following the intervention for 42 subjects. No subject identifiers were included, so we don't know who these scores belong to, but we do have demographics for these subjects.
I'm not quite sure how to go about using the data from the third test, or if I even should use it. Some people have suggested I do a one-way ANOVA and ignore the independence of observations assumption, but that seems less than ideal. Do you all have any advice on how to proceed?
Pre and immediate post-test data:
Three month data:
Thank you very much!
The data are pre and post-intervention test scores for an educational intervention, which I was planning on analyzing with repeated-measures ANOVA. The immediate pre and post scores are recorded with associated subject identifiers (n=100).
I was later sent data from a third test administered three months following the intervention for 42 subjects. No subject identifiers were included, so we don't know who these scores belong to, but we do have demographics for these subjects.
I'm not quite sure how to go about using the data from the third test, or if I even should use it. Some people have suggested I do a one-way ANOVA and ignore the independence of observations assumption, but that seems less than ideal. Do you all have any advice on how to proceed?
Pre and immediate post-test data:
Code:
* Example generated by -dataex-. For more info, type help dataex clear input byte(Subno sex age race specialty discipline ftzskin ConFL1 ConFD1 ConFL2 ConFD2 score overall1 overall2 cancer1 cancer2 inflamm1 inflamm2 infect1 infect2 soc1 soc2 LSS1 DSS1 LSS2 DSS2) 1 1 3 1 3 4 2 5 3 5 3 77 39 38 6 5 15 15 10 10 8 8 20 19 20 18 2 0 2 1 3 4 2 5 4 5 5 78 39 39 6 6 16 16 9 9 8 8 19 20 19 20 3 1 2 1 3 3 2 5 5 5 5 70 35 35 6 6 15 14 6 7 8 8 17 18 18 17 4 1 3 3 3 3 4 5 3 5 4 78 39 39 6 6 16 16 9 9 8 8 20 19 20 19 5 0 4 1 2 4 3 3 3 3 3 66 31 35 4 5 12 14 7 8 8 8 17 14 19 16 6 0 2 2 3 3 6 4 3 4 3 76 38 38 5 4 16 16 9 10 8 8 18 20 19 19 7 0 3 1 1 1 1 3 2 3 3 53 23 30 4 5 11 13 6 6 2 6 14 9 17 13 8 1 . 1 2 6 3 3 3 3 3 52 25 27 5 3 11 12 4 6 5 6 14 11 15 12 9 1 3 1 2 4 4 4 3 4 4 46 23 23 2 3 11 9 4 5 6 6 13 10 11 12 10 0 2 4 2 3 4 2 1 2 2 58 31 27 5 6 11 10 8 5 7 6 17 14 13 14 11 0 2 4 2 4 4 3 2 3 3 54 26 28 5 4 11 12 4 4 6 8 13 13 15 13 12 0 2 1 2 3 4 3 2 3 3 60 30 30 5 3 12 16 5 3 8 8 15 15 16 14 13 0 2 3 3 6 4 2 2 3 3 45 23 22 4 3 10 12 2 2 7 5 14 9 12 10 14 1 2 1 3 3 3 4 3 4 3 79 39 40 5 6 16 16 10 10 8 8 19 20 20 20 15 1 3 3 2 3 4 2 2 2 2 64 30 34 3 4 12 15 8 7 7 8 17 13 18 16 16 0 5 1 1 4 1 3 2 3 3 64 31 33 5 4 13 13 7 8 6 8 18 13 18 15 17 0 2 1 3 5 2 2 1 3 2 41 16 25 2 2 6 11 1 5 7 7 11 5 13 12 18 1 3 3 5 4 3 3 2 3 3 45 23 22 2 3 10 10 3 4 8 5 11 12 13 9 19 0 4 4 6 4 4 3 3 3 3 65 32 33 4 5 13 13 8 7 7 8 18 14 19 14 20 1 3 1 5 3 2 2 2 2 2 60 30 30 4 5 12 12 6 5 8 8 17 13 17 13 21 0 2 1 4 3 1 3 2 3 3 64 31 33 5 5 11 14 7 6 8 8 17 14 18 15 22 0 2 5 4 3 2 3 1 4 3 53 24 29 4 6 9 13 4 3 7 7 12 12 15 14 23 1 2 1 5 3 3 2 2 3 3 55 23 32 5 5 10 15 4 5 4 7 13 10 18 14 24 0 3 1 5 4 3 3 1 3 2 55 24 31 3 4 10 13 3 6 8 8 13 11 16 15 25 1 2 1 5 3 4 3 2 3 3 41 21 20 3 3 7 7 4 2 7 8 12 9 10 10 26 0 2 1 6 3 4 2 1 3 2 52 25 27 3 3 9 11 7 5 6 8 13 12 16 11 27 1 3 1 5 4 2 3 2 3 3 59 28 31 4 4 12 12 6 7 6 8 14 14 15 16 28 0 4 4 2 4 3 3 3 3 3 54 25 29 2 4 12 14 4 4 7 7 14 11 16 13 29 1 2 1 5 4 2 3 2 3 2 51 24 27 4 3 11 12 5 6 4 6 14 10 15 12 30 0 2 2 2 3 5 2 1 3 3 47 22 25 4 6 7 8 5 3 6 8 12 10 14 11 31 1 2 3 4 3 3 2 2 3 3 51 23 28 4 4 7 9 7 7 5 8 14 9 17 11 32 0 2 3 3 5 2 1 1 1 1 33 14 19 2 4 4 6 2 3 6 6 9 5 9 10 33 0 3 3 3 4 3 5 4 5 4 75 36 39 4 5 14 16 10 10 8 8 18 18 20 19 34 0 2 1 6 2 1 2 1 3 2 51 24 27 3 4 9 12 5 3 7 8 12 12 15 12 35 0 . 1 6 2 3 2 1 2 2 40 18 22 2 4 5 7 6 6 5 5 6 12 11 11 36 0 2 2 2 2 6 4 3 5 5 58 31 27 4 4 12 11 8 5 7 7 16 15 13 14 37 0 2 1 3 2 3 3 1 4 3 64 29 35 4 5 11 14 7 9 7 7 16 13 18 17 38 0 3 1 3 5 3 2 1 2 1 41 22 19 4 3 8 10 3 0 7 6 9 13 9 10 39 0 4 1 1 1 2 2 2 3 3 55 26 29 3 5 11 12 5 4 7 8 15 11 16 13 40 0 2 1 6 1 2 3 3 3 3 57 27 30 5 6 6 9 8 7 8 8 15 12 16 14 41 0 . 1 1 1 2 4 4 4 4 69 34 35 6 6 13 13 7 8 8 8 18 16 19 16 42 0 3 1 6 1 4 3 3 3 3 53 21 32 3 5 7 13 5 7 6 7 13 8 19 13 43 0 2 1 2 1 3 2 1 2 2 43 21 22 4 5 9 7 3 4 5 6 11 10 12 10 44 0 2 1 6 1 1 4 2 4 3 53 21 32 4 4 6 13 5 7 6 8 13 8 18 14 45 0 2 1 5 4 2 4 2 3 3 45 20 25 2 3 7 10 5 5 6 7 12 8 14 11 46 0 3 1 6 1 2 3 2 3 2 60 30 30 5 4 12 11 5 7 8 8 17 13 16 14 47 0 3 5 6 1 2 2 1 2 2 48 25 23 3 3 8 9 6 3 8 8 12 13 12 11 48 1 3 1 6 1 2 1 1 2 2 26 9 17 1 4 4 7 2 1 2 5 6 3 9 8 49 0 3 2 2 1 4 1 1 2 2 26 10 16 2 2 4 6 1 3 3 5 7 3 9 7 50 1 3 1 1 1 3 1 1 2 2 46 22 24 3 3 10 12 3 3 6 6 11 11 13 11 51 0 2 1 3 5 2 2 2 3 3 58 29 29 4 4 12 12 6 6 7 7 17 12 17 12 52 0 3 1 6 1 2 4 3 4 3 62 29 33 4 5 10 13 7 7 8 8 17 12 19 14 53 0 2 4 4 3 5 2 1 3 2 48 23 25 4 4 9 12 5 3 5 6 12 11 12 13 54 1 3 1 6 1 1 3 3 3 2 46 18 28 5 5 5 11 3 5 5 7 8 10 14 14 55 0 3 3 1 1 3 2 1 2 2 66 31 35 4 6 15 15 6 6 6 8 16 15 19 16 56 1 5 1 5 4 2 3 2 3 2 50 24 26 4 4 8 10 6 6 6 6 14 10 13 13 57 0 2 4 4 3 1 2 1 4 3 55 26 29 4 5 12 12 5 4 5 8 15 11 15 14 58 0 4 1 6 1 1 1 1 2 2 47 19 28 2 3 7 11 5 6 5 8 12 7 16 12 59 0 4 1 1 1 2 1 1 3 3 35 4 31 2 5 0 13 2 6 0 7 2 2 18 13 60 0 2 1 6 3 2 2 1 2 2 64 30 34 5 5 12 12 7 9 6 8 14 16 16 18 61 0 3 4 1 1 2 2 2 3 2 39 17 22 1 4 7 9 4 3 5 6 12 5 14 8 62 0 3 3 4 1 2 4 3 4 3 36 18 18 5 3 6 6 3 3 4 6 8 10 10 8 63 0 4 1 4 1 2 2 1 2 2 50 23 27 5 4 7 11 5 5 6 7 13 10 13 14 64 1 2 1 4 3 2 3 2 3 3 54 24 30 4 4 9 11 6 7 5 8 13 11 15 15 65 0 3 1 6 2 2 2 1 2 1 59 27 32 3 4 12 14 7 6 5 8 15 12 17 15 66 1 2 1 4 3 1 2 1 3 2 61 31 30 4 3 11 12 9 7 7 8 15 16 16 14 67 0 2 4 6 2 5 4 2 3 2 55 25 30 3 5 10 12 5 5 7 8 14 11 15 15 68 0 2 1 4 6 3 3 3 4 3 57 25 32 4 4 10 14 5 6 6 8 15 10 17 15 69 0 2 2 6 3 5 3 2 3 2 53 25 28 3 3 10 12 6 5 6 8 14 11 15 13 70 1 . 1 1 2 1 3 1 3 2 53 23 30 4 4 9 12 3 6 7 8 12 11 15 15 71 0 2 1 6 1 3 3 2 3 3 55 24 31 4 4 8 14 6 5 6 8 14 10 17 14 72 0 5 1 6 1 1 1 1 2 2 63 31 32 3 4 14 14 7 7 7 7 18 13 19 13 73 0 3 2 1 1 5 2 1 2 2 59 28 31 3 4 13 14 6 5 6 8 15 13 16 15 74 0 4 1 1 1 2 4 3 4 3 54 25 29 4 4 10 15 4 5 7 5 16 9 18 11 75 0 3 1 4 1 3 2 1 2 2 46 22 24 3 2 9 12 4 4 6 6 13 9 12 12 76 1 3 1 1 1 2 1 1 2 2 47 20 27 2 4 9 13 3 4 6 6 12 8 16 11 77 0 2 4 1 1 4 2 2 2 2 56 26 30 6 6 9 11 6 6 5 7 14 12 17 13 78 0 2 4 4 3 4 4 2 3 3 50 25 25 3 2 10 11 6 5 6 7 13 12 14 11 79 1 3 3 2 1 3 3 3 3 3 60 28 32 3 4 12 14 6 6 7 8 17 11 17 15 80 0 3 1 4 1 2 4 2 4 3 66 32 34 4 4 14 14 7 8 7 8 19 13 19 15 81 0 5 1 6 1 1 2 2 2 2 38 13 25 1 5 7 10 3 5 2 5 9 4 14 11 82 0 5 1 3 4 3 4 4 4 4 78 39 39 5 5 16 16 10 10 8 8 20 19 20 19 83 0 4 1 6 1 2 2 1 3 3 29 13 16 3 3 7 6 2 1 1 6 10 3 8 8 84 1 3 1 4 1 2 2 1 3 3 45 19 26 2 3 8 11 4 5 5 7 9 10 12 14 85 0 2 1 6 1 2 3 2 3 2 56 27 29 6 6 8 10 6 7 7 6 15 12 15 14 86 0 2 1 2 4 1 3 1 3 3 49 20 29 3 5 8 13 4 4 5 7 12 8 15 14 87 0 3 1 6 1 2 3 1 3 3 51 25 26 3 4 11 12 6 5 5 5 11 14 14 12 88 0 3 1 4 1 2 1 1 2 2 33 14 19 3 3 3 7 2 1 6 8 7 7 9 10 89 0 3 4 6 1 3 2 2 3 3 40 15 25 1 5 3 8 5 4 6 8 10 5 15 10 90 0 2 1 3 2 1 3 1 3 2 67 32 35 4 4 15 15 5 8 8 8 17 15 18 17 91 0 2 1 4 1 3 2 1 3 2 36 13 23 1 5 8 11 2 2 2 5 10 3 12 11 92 0 2 1 4 3 1 3 2 3 2 58 29 29 3 3 12 12 6 6 8 8 15 14 16 13 93 0 2 1 5 3 1 2 3 2 2 60 28 32 4 5 10 12 7 7 7 8 16 12 19 13 94 0 4 5 5 4 2 3 2 3 2 67 34 33 5 5 14 16 8 7 7 5 19 15 16 17 95 0 2 4 1 1 3 2 1 2 2 56 28 28 5 5 9 9 6 6 8 8 13 15 13 15 96 0 2 1 4 2 2 3 2 3 3 47 18 29 3 4 4 12 5 6 6 7 12 6 15 14 97 1 . 5 6 2 3 2 1 3 3 30 11 19 2 4 2 6 3 2 4 7 5 6 10 9 98 0 2 5 4 3 5 2 1 3 2 47 21 26 3 6 10 10 3 2 5 8 12 9 15 11 99 0 2 1 6 1 3 2 2 2 2 38 18 20 3 3 8 9 1 1 6 7 10 8 10 10 100 0 2 2 1 1 5 2 1 2 1 60 30 30 4 4 14 14 4 4 8 8 16 14 16 14 end label values sex sex label def sex 0 "Female", modify label def sex 1 "Male", modify label values age age label def age 2 "25-34 years", modify label def age 3 "35-44 years", modify label def age 4 "45-54 years", modify label def age 5 "55-64 years", modify label values race race label def race 1 "White", modify label def race 2 "Black", modify label def race 3 "Latino", modify label def race 4 "Asian", modify label def race 5 "Other", modify label values specialty specialty label def specialty 1 "Family Medicine", modify label def specialty 2 "Internal Medicine", modify label def specialty 3 "Dermatology", modify label def specialty 4 "Pediatrics", modify label def specialty 5 "Emergency Medicine", modify label def specialty 6 "Other", modify label values discipline discipline label def discipline 1 "Advanced Practice Provider", modify label def discipline 2 "Medical Student", modify label def discipline 3 "Resident", modify label def discipline 4 "Attending", modify label def discipline 5 "Nurse", modify label def discipline 6 "Other", modify
Three month data:
Code:
* Example generated by -dataex-. For more info, type help dataex clear input byte(age discipline race sex specialty CancerDSS3 CancerLSS3 ConfD3 ConfL3 DSS3 InfectDSS3 InfectLSS3 InflamDSS3 InflamLSS3 LSS3 Overall3 SOCDSS3 SOCLSS3) 2 3 4 1 3 3 3 4 5 20 5 5 8 8 20 40 4 4 4 1 1 0 1 0 0 . . 0 0 0 0 0 0 0 0 0 3 1 2 1 2 1 2 2 2 4 1 1 0 1 7 11 2 3 5 4 1 0 2 2 3 3 3 13 3 4 5 6 17 30 3 4 3 1 1 1 . 0 2 3 3 7 2 3 3 6 14 21 2 3 3 1 1 1 . 0 0 . . 0 0 0 0 0 0 0 0 0 4 4 1 1 2 1 3 2 2 12 3 3 4 6 16 28 4 4 2 5 1 1 3 1 3 1 1 10 2 3 3 4 12 22 4 2 3 4 1 0 2 2 2 3 4 12 3 3 4 6 15 27 3 4 2 3 3 0 4 2 2 2 2 11 3 3 3 5 14 25 3 4 2 4 4 1 2 2 2 3 3 13 2 2 5 6 14 27 4 4 5 4 1 0 5 3 2 2 3 13 2 4 5 4 13 26 3 3 2 3 1 1 . 3 3 1 2 13 3 3 4 4 13 26 3 3 2 2 4 1 4 0 1 . . 1 0 0 1 0 1 2 0 0 2 3 1 0 3 3 3 3 3 19 4 4 8 8 19 38 4 4 2 3 4 1 4 2 2 2 3 10 1 3 4 6 14 24 3 3 3 4 3 1 3 3 2 3 4 20 5 5 8 8 19 39 4 4 5 4 1 1 1 2 2 2 3 16 4 5 6 8 19 35 4 4 4 4 1 0 5 1 3 2 3 11 3 3 4 6 16 27 3 4 2 3 1 1 2 3 3 2 2 19 5 4 7 6 17 36 4 4 2 3 . 1 4 2 2 2 3 15 2 2 7 7 15 30 4 4 2 4 1 1 3 3 3 3 5 20 5 4 8 8 19 39 4 4 2 3 1 1 4 2 2 3 3 16 3 4 7 6 16 32 4 4 2 3 2 1 2 2 1 3 3 12 2 4 4 6 14 26 4 3 2 3 2 1 . 2 1 2 2 13 4 2 4 5 12 25 3 4 2 1 4 1 1 2 3 2 2 12 2 4 5 7 17 29 3 3 5 1 1 1 4 1 2 2 2 13 2 5 6 7 17 30 4 3 2 3 4 1 4 1 3 2 3 10 2 2 4 5 13 23 3 3 2 1 2 1 1 1 3 2 2 14 2 2 7 7 16 30 4 4 2 1 2 1 1 0 0 . . 0 0 0 0 0 0 0 0 0 2 1 1 1 . 3 3 2 3 16 4 3 6 4 13 29 3 3 2 1 1 1 . 1 3 2 3 11 2 2 5 7 15 26 3 3 2 3 4 1 4 1 2 3 3 15 3 4 7 6 15 30 4 3 3 6 1 1 5 3 3 3 4 16 3 4 6 8 19 35 4 4 3 1 1 0 4 2 2 1 1 12 4 2 4 4 10 22 2 2 2 3 1 1 3 2 2 2 4 17 4 3 7 8 16 33 4 3 2 3 1 1 4 1 3 2 3 13 3 3 5 5 14 27 4 3 3 1 1 1 4 1 0 2 3 10 2 0 4 4 8 18 3 4 2 1 4 1 1 2 3 1 1 14 3 2 5 4 13 27 4 4 2 1 1 1 4 2 0 2 2 7 1 2 3 5 8 15 1 1 end label values age age label def age 2 "25-34 years", modify label def age 3 "35-44 years", modify label def age 4 "45-54 years", modify label def age 5 "55-64 years", modify label values discipline discipline label def discipline 1 "Advanced Practice Provider", modify label def discipline 2 "Medical Student", modify label def discipline 3 "Resident", modify label def discipline 4 "Attending", modify label def discipline 5 "Nurse", modify label def discipline 6 "Other", modify label values race race label def race 1 "White", modify label def race 2 "Black", modify label def race 3 "Latino", modify label def race 4 "Asian", modify label values sex sex label def sex 0 "Female", modify label def sex 1 "Male", modify label values specialty specialty label def specialty 1 "Family Medicine", modify label def specialty 2 "Internal Medicine", modify label def specialty 3 "Dermatology", modify label def specialty 4 "Pediatrics", modify label def specialty 5 "Emergency Medicine", modify
Thank you very much!
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