EPI 202 Lab 2.docx - EPI 202 Lab 2 1 In a study of malnutrition and diarrhea in children under age five in the Sudan 154 episodes of diarrhea were

EPI 202 Lab 2.docx - EPI 202 Lab 2 1 In a study of...

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EPI 202 Lab 21.In a study of malnutrition and diarrhea in children under age five in the Sudan, 154 episodes of diarrhea were observed in 38.51 person-years of observation among children who were 75% or less of their expected weight for age, and 287 episodes of diarrhea were observed in 88.83 person-years of observation among children who were 90% or more of their expected weight for age (El Samani et al.; Am J Epidemiol, 1988). Suppose the data from this study were broken down by sex as follows: Male< 75% WFA> 90%WTAFemale< 75% WFA> 90% WFACases75150Cases79137PY20.548PY18.0140.83a.Calculate the summary incidence rate ratio for the association between weight for age and rate of diarrhea. Interpret your answer.^IRRMH=aiN0iTibiN1iTi=75×4868.5+79×40.8358.84150×20.568.5+137×18.0158.84=52.55+54.8244.89+41.93=107.486.82=1.24After adjusting for sex, the IR of diarrhea among children who are less than 75% of their expected weight for age is 1.24 times higher than IR of diarrheaamong children who are 90% or more of their expected weight for age, assuming no residual confounding, confounding by other variables, selectionbias, or information bias.b.Calculate the summary incidence rate difference for the association betweenweight for age and rate of diarrhea. Interpret your answer.^IRDmale=3.65853.125=0.5335^IRDfemale=4.3863.355=1.031^VAR(^IRDmale)=aN12+bN02=75420.25+1502304=0.1784+0.0651=0.2435^VAR(^IRDfemale)=aN12+bN02=79324.4+1371667=0.2435+0.0822=0.3257^IRDINV VAR=wi'^IRDiwi'=0.53350.2435+1.0310.325710.2435+10.3257=2.191+3.1654.107+3.070=5.3567.177=0.746After adjusting for sex, the IR of diarrhea among children who are less than 75% of their expected weight for age is 0.746 per person-year more than the IR of diarrhea among children who are more than 90% of their expected weight for age, assuming no residual confounding, confounding by other variables, selection bias, or information bias.c.Test the hypothesis that weight for age has no association with rate of diarrhea, after stratifying by sex. Interpret the numeric results. H0: There is no association between weight for age and the rate of diarrhea, after stratifying by sex.HA: There is an association between weight for age and the rate of diarrhea, after stratifying by sex.
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Z2=[i=1IXii=1IEi(Xi|H0)]2i=1IVari(Xi|H0)x12Xi=ai=75+79=154Ei(Xi|H0)=M1iN1iTi=67.34+66.11=133.45Vari(Xi|H0)=M1iN1iN0iTi2=47.18+45.88=93.06Z2=[154133.45]293.06=4.54x12Pr[x12>4.54]=0.0324<0.05These data are not consistent with the state of nature described by the null.
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