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Bivariate Versus Multivariate Management Case Assignment (Case Study Sample)




Bivariate Versus Multivariate
Bivariate Versus Multivariate
When examining the existing relationship between the explanatory factor and the outcome, it is important to note the factors that modify the factor's effects on the outcome or effect modifiers. Besides, it is important to note the potential confounding or bias in the study since these results may cause a reported association or lack thereof which are misleading. Therefore, both bias and confounding factors related to the measurement of a given study design (Warner, 2008).
Question 1: Identify variables from Table 1 that should be further analyzed (to rule out whether they are confounders or effect modifiers). Briefly, provide rationale.
A confounding factor comes in a given situation in which the association between the exposure and outcome becomes distorted due to the presence of another variable. Therefore, a positive confounding comes when the observable relationship is biased away from the null while the negative confounding is when the apparent association is biased towards the null (Warner, 2008).
Separately, effect modification is when a variable either positively or negatively or both modifies the outcome or effect or the risk factor. For example, Gene Y (-20.5%), Gene Z (-33%), and Gene T (85%) will be taken for further analysis since they have an uneven distribution between the groups hence distort the existing relationship between the result and the primary exposure. Besides, the presence of risks such as crude OR and adjustment OR, the confounding factors have a change in estimated measures more than 10 percent (with a Mantel-Haenszel equation). Thus, the pooled estimates of Gene Y, Z and T are more than 10 percent of the crude estimates. Separately, the estimates differ from one another and are both less and more significant than the crude estimate hence they have both confounding and effect modifications. For example, adjustment OR in Gene T is more than crude OR estimate while genes Z and Y have adjustments OR less than Crude OR estimates (Warner, 2008).
Question 2: Stratified analysis was conducted on one of the genes in Table 1 and odds ratios were obtained. What do these results suggest: Drug A=0: OR=2.2 for birth defect given presence of gene, Drug A=1: OR=1.4 for birth defect given presence of gene
The results indicated in the question above show a two-by-two frequency epidemiology that explores the association between the exposure to risk factors and the disease or other outcomes. Therefore, the tests indicate odds ratio with relative risk larger or smaller than 1.0. Thus, the Drug A =0: OR=2.2 shows a stronger association which is further or broader than A=1: OR=1.4 since the former has a statistical significance with p-value becoming smaller <0.05. Contrarily the latter A=0: OR=1.4 has a more significant p-value than the <0.05.Therefore, Drug A=0: OR=2.2 result to congenital disabilities given the presence of gene than A=1: OR=1.4. Thus, there were confounding factors to congenital disabilities in the presence of gene in A=0: OR=2.2 since the values are less than the crude OR for most of the variables especially Genes Y, Z and T (Warner, 2008).
Question 3: Critically review the following controversial paper published (and later retracted) by Wakefield et al., which implicated MMR vaccine as a possible etiologic contributor to Autism, etc. You may use either version for your review. D

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