Wang, Xiaoqin; Jin, Yin; Yin, Li Point and interval estimations of marginal risk difference by logistic model. (English) Zbl 1330.62100 Commun. Stat., Theory Methods 44, No. 17, 3703-3722 (2015). Summary: We use logistic model to get point and interval estimates of the marginal risk difference in observational studies and randomized trials with dichotomous outcome. We prove that the maximum likelihood estimate of the marginal risk difference is unbiased for finite sample and highly robust to the effects of dispersing covariates. We use approximate normal distribution of the maximum likelihood estimates of the logistic model parameters to get approximate distribution of the maximum likelihood estimate of the marginal risk difference and then the interval estimate of the marginal risk difference. We illustrate application of the method by a real medical example. Cited in 1 Document MSC: 62F10 Point estimation 62E17 Approximations to statistical distributions (nonasymptotic) 62P10 Applications of statistics to biology and medical sciences; meta analysis 62J02 General nonlinear regression Keywords:confounding covariate; interval estimate; logistic model; marginal risk difference; point estimate PDFBibTeX XMLCite \textit{X. Wang} et al., Commun. Stat., Theory Methods 44, No. 17, 3703--3722 (2015; Zbl 1330.62100) Full Text: DOI References: [1] Altham P., J. Roy. Statist. Soc. B 46 pp 118– (1984) [2] DOI: 10.1002/sim.2781 · doi:10.1002/sim.2781 [3] DOI: 10.1002/sim.2618 · doi:10.1002/sim.2618 [4] Azzalini A., Statistical Inference Based On The Likelihood (1996) · Zbl 0871.62001 [5] DOI: 10.1002/(SICI)1097-0258(20000515)19:9<1141::AID-SIM479>3.0.CO;2-F · doi:10.1002/(SICI)1097-0258(20000515)19:9<1141::AID-SIM479>3.0.CO;2-F [6] DOI: 10.1093/aje/kwm223 · doi:10.1093/aje/kwm223 [7] DOI: 10.1017/CBO9780511802843 · doi:10.1017/CBO9780511802843 [8] DOI: 10.1093/biomet/71.3.431 · Zbl 0565.62094 · doi:10.1093/biomet/71.3.431 [9] DOI: 10.1111/j.0006-341X.1999.00652.x · Zbl 1059.62654 · doi:10.1111/j.0006-341X.1999.00652.x [10] DOI: 10.1093/aje/kwh221 · doi:10.1093/aje/kwh221 [11] DOI: 10.1093/ije/15.3.413 · doi:10.1093/ije/15.3.413 [12] DOI: 10.1214/ss/1009211805 · Zbl 1059.62506 · doi:10.1214/ss/1009211805 [13] DOI: 10.2307/2530043 · doi:10.2307/2530043 [14] DOI: 10.1214/088342304000000305 · Zbl 1100.62591 · doi:10.1214/088342304000000305 [15] Lindsey J.K., Parametric Statistical Inference (1996) · Zbl 0855.62002 [16] DOI: 10.1007/978-1-4899-3242-6 · Zbl 0588.62104 · doi:10.1007/978-1-4899-3242-6 [17] DOI: 10.1111/j.1523-5378.2008.00628.x · doi:10.1111/j.1523-5378.2008.00628.x [18] DOI: 10.2307/2335942 · doi:10.2307/2335942 [19] DOI: 10.1007/978-1-4757-2443-1 · doi:10.1007/978-1-4757-2443-1 [20] DOI: 10.1198/016214504000001880 · Zbl 1117.62418 · doi:10.1198/016214504000001880 [21] DOI: 10.1093/aje/kwi188 · doi:10.1093/aje/kwi188 [22] DOI: 10.1002/sim.3811 · doi:10.1002/sim.3811 [23] DOI: 10.2307/1912526 · Zbl 0478.62088 · doi:10.2307/1912526 [24] DOI: 10.1007/978-3-642-95461-0_1 · doi:10.1007/978-3-642-95461-0_1 [25] DOI: 10.1093/aje/kwh090 · doi:10.1093/aje/kwh090 This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.