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h5 指数:50
h5 中位数:83

h5 指数是指在过去整整 5 年中所发表文章的 h 指数。h 指在 2017-2021 年间发表的 h 篇文章每篇至少都被引用过 h 次的最大值。隐藏

出版物的 h5 中位数，是指出版物的 h5 指数所涵盖的所有文章获得的引用次数的中位值。隐藏

#6 Probability & Statistics with Applications

标题/作者	引用次数	年份
Using simulation studies to evaluate statistical methods TP Morris, IR White, MJ Crowther Statistics in Medicine 38 (11), 2074-2102	526	2019
Practical recommendations for reporting F ine‐G ray model analyses for competing risk data PC Austin, JP Fine Statistics in Medicine 36 (27), 4391-4400	457	2017
A framework for the investigation of pleiotropy in two‐sample summary data Mendelian randomization J Bowden, F Del Greco M, C Minelli, G Davey Smith, N Sheehan, ... Statistics in Medicine 36 (11), 1783-1802	440	2017
Intermediate and advanced topics in multilevel logistic regression analysis PC Austin, J Merlo Statistics in Medicine 36 (20), 3257-3277	332	2017
Minimum sample size for developing a multivariable prediction model: PART II‐binary and time‐to‐event outcomes RD Riley, KIE Snell, J Ensor, DL Burke, FE Harrell Jr, KGM Moons, ... Statistics in Medicine 38 (7), 1276-1296	329	2019
Meta‐analysis using individual participant data: one‐stage and two‐stage approaches, and why they may differ DL Burke, J Ensor, RD Riley Statistics in Medicine 36 (5), 855-875	298	2017
Bootstrap inference when using multiple imputation M Schomaker, C Heumann Statistics in Medicine 37 (14), 2252-2266	250	2018
Tutorial in biostatistics: data‐driven subgroup identification and analysis in clinical trials I Lipkovich, A Dmitrienko, R B D'Agostino Sr Statistics in Medicine 36 (1), 136-196	210	2017
Extending the MR‐Egger method for multivariable Mendelian randomization to correct for both measured and unmeasured pleiotropy JMB Rees, AM Wood, S Burgess Statistics in Medicine 36 (29), 4705-4718	156	2017
Firth's logistic regression with rare events: accurate effect estimates and predictions? R Puhr, G Heinze, M Nold, L Lusa, A Geroldinger Statistics in Medicine 36 (14), 2302-2317	150	2017
Analysis of small sample size studies using nonparametric bootstrap test with pooled resampling method AK Dwivedi, I Mallawaarachchi, LA Alvarado Statistics in Medicine 36 (14), 2187-2205	134	2017
Some methods for heterogeneous treatment effect estimation in high dimensions S Powers, J Qian, K Jung, A Schuler, NH Shah, T Hastie, R Tibshirani Statistics in Medicine 37 (11), 1767-1787	127	2018
A comparison of seven random‐effects models for meta‐analyses that estimate the summary odds ratio D Jackson, M Law, T Stijnen, W Viechtbauer, IR White Statistics in Medicine 37 (7), 1059-1085	126	2018
Standard errors and confidence intervals for variable importance in random forest regression, classification, and survival H Ishwaran, M Lu Statistics in Medicine 38 (4), 558-582	123	2019
Unbiased split variable selection for random survival forests using maximally selected rank statistics MN Wright, T Dankowski, A Ziegler Statistics in Medicine 36 (8), 1272-1284	112	2017
Combining randomized and non‐randomized evidence in network meta‐analysis O Efthimiou, D Mavridis, TPA Debray, M Samara, M Belger, GCM Siontis, ... Statistics in Medicine 36 (8), 1210-1226	109	2017
Measures of clustering and heterogeneity in multilevel P oisson regression analyses of rates/count data PC Austin, H Stryhn, G Leckie, J Merlo Statistics in Medicine 37 (4), 572-589	105	2018
Random effects meta‐analysis: Coverage performance of 95% confidence and prediction intervals following REML estimation C Partlett, RD Riley Statistics in Medicine 36 (2), 301-317	100	2017
Modeling continuous response variables using ordinal regression Q Liu, BE Shepherd, C Li, FE Harrell Jr Statistics in Medicine 36 (27), 4316-4335	100	2017
Minimum sample size for developing a multivariable prediction model: Part I–Continuous outcomes RD Riley, KIE Snell, J Ensor, DL Burke, FE Harrell Jr, KGM Moons, ... Statistics in Medicine 38 (7), 1262-1275	91	2019

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