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Under our incidence density case sampling strategy exponentiation of conditional logistic regression model coefficients and their corresponding 95% confidence intervals (95% CI) provided unbiased odds ratio (OR) estimates of the underlying population incidence rate ratio [ 41].
This approach was designed to ensure that the sample of control spouses would have similar smoking habits as those in the study base; hence, differences between the recorded proportion of smokers in the case and control group can be used to calculate unbiased odds ratios.
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Third, we give detailed guidance for how to use the observed data to draw conclusions about the missingness mechanism(s) and thereby to help decide whether CRA logistic regression will produce an asymptotically unbiased exposure odds ratio estimate.
The results have important implications for the analysis of epidemiologic studies suffering from missing data: In some settings where researchers might believe a CRA is biased due to data not being MCAR, a CRA logistic regression analysis may in fact produce asymptotically unbiased exposure odds ratio estimates.
Unbiased estimates of odds ratios detected by GWA studies are typically in the range of 1.1 1.3; to have good power to detect such effect sizes requires many thousands of samples, which is beyond the reach of the autism genetics community at the moment.
Since risk set sampling controls were used, the odds ratios are unbiased estimates of the corresponding rate ratios.
‡Median unbiased estimate of the odds ratio.
Median unbiased estimates of the odds ratio were reported when warranted.
Otherwise, previous simulations studies support the use of IPTW estimators as approximately unbiased estimators of marginal odds ratios [ 22, 38].
We performed descriptive statistical analysis and exact conditional logistic regression to compute the most likely estimate or, when small cell sizes required, the median unbiased estimate of matched odds ratios (mORs) with 95% confidence intervals (CIs).
At the third interim analysis, the sample path crossed the upper boundary and the trial was stopped, the cure-markedly effective rates were 45% for IFCS group and 67% for IFCA group, respectively, the one-sided p-value was 0.0036, the median unbiased estimate of the odds ratio (OR) for the benefit of IFCA relative to IFCS was 2.91 with 95%CI: 1.40 to 6.06.
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