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標(biāo)題: Titlebook: Applied Multiple Imputation; Advantages, Pitfalls Kristian Kleinke,Jost Reinecke,Martin Spiess Textbook 2020 Springer Nature Switzerland AG [打印本頁(yè)]

作者: controllers    時(shí)間: 2025-3-21 18:36
書(shū)目名稱Applied Multiple Imputation影響因子(影響力)




書(shū)目名稱Applied Multiple Imputation影響因子(影響力)學(xué)科排名




書(shū)目名稱Applied Multiple Imputation網(wǎng)絡(luò)公開(kāi)度




書(shū)目名稱Applied Multiple Imputation網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書(shū)目名稱Applied Multiple Imputation被引頻次




書(shū)目名稱Applied Multiple Imputation被引頻次學(xué)科排名




書(shū)目名稱Applied Multiple Imputation年度引用




書(shū)目名稱Applied Multiple Imputation年度引用學(xué)科排名




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作者: hypnogram    時(shí)間: 2025-3-21 22:43
2199-7357 ls in R with supplementary R code and data sets.Discusses thThis book explores missing data techniques and provides a detailed and easy-to-read introduction to multiple imputation, covering the theoretical aspects of the topic and offering hands-on help with the implementation. It discusses the pros
作者: RADE    時(shí)間: 2025-3-22 03:06
Untersuchungsdesign und Methodik,d with simple examples. In addition, conditions are given for analysing data sets without the need to explicitly model the missing data mechanism (“ignorability”). We also review diagnostic tools for incomplete data sets, both descriptive and based on a statistical test.
作者: 碌碌之人    時(shí)間: 2025-3-22 07:46
Untersuchungsdesign und Methodik,ve practical advice which procedure might be suited best in a given scenario because valid inferences in applied research can only be expected based on informed decisions. A conclusion of this chapter will be that there is not the one method or technique that works best under every possible scenario.
作者: limber    時(shí)間: 2025-3-22 12:00
Untersuchungsdesign und Methodik,modeling approach, where only univariate marginal models are used to generate imputations. Additional topics are rounding, how to deal with restrictions and how to treat interaction or higher polynomial terms.
作者: FLAGR    時(shí)間: 2025-3-22 13:33
Missing Data Mechanism and Ignorability,d with simple examples. In addition, conditions are given for analysing data sets without the need to explicitly model the missing data mechanism (“ignorability”). We also review diagnostic tools for incomplete data sets, both descriptive and based on a statistical test.
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作者: AVID    時(shí)間: 2025-3-23 00:31
Multiple Imputation: Theory,modeling approach, where only univariate marginal models are used to generate imputations. Additional topics are rounding, how to deal with restrictions and how to treat interaction or higher polynomial terms.
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作者: FOLD    時(shí)間: 2025-3-23 12:51
Untersuchungsdesign und Methodik, nonresponse, unit nonresponse and attrition, and review the most common statistical approaches to inference from samples to populations. Missing data patterns (univariate, monotone, arbitrary) are described as far as they are relevant for choosing an appropriate technique to compensate for missing
作者: 流浪者    時(shí)間: 2025-3-23 14:33
Untersuchungsdesign und Methodik,t random (MAR) or missing not at random (MNAR) is introduced. Consequences of different possible missing data mechanisms are considered and illustrated with simple examples. In addition, conditions are given for analysing data sets without the need to explicitly model the missing data mechanism (“ig
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作者: Dawdle    時(shí)間: 2025-3-23 22:38
Untersuchungsdesign und Methodik,ed on monotone and non-monotone missing patterns, the approach based on joint modeling of all variables with missing values and the fully conditional modeling approach, where only univariate marginal models are used to generate imputations. Additional topics are rounding, how to deal with restrictio
作者: 幻影    時(shí)間: 2025-3-24 02:35

作者: 鞭子    時(shí)間: 2025-3-24 08:27
Kristian Kleinke,Jost Reinecke,Martin SpiessProvides an introduction to missing data and multiple imputation for students and applied researchers.Features numerous step-by-step tutorials in R with supplementary R code and data sets.Discusses th
作者: 尋找    時(shí)間: 2025-3-24 13:42
Statistics for Social and Behavioral Scienceshttp://image.papertrans.cn/a/image/159973.jpg
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作者: instill    時(shí)間: 2025-3-25 15:40
Introduction and Basic Concepts, nonresponse, unit nonresponse and attrition, and review the most common statistical approaches to inference from samples to populations. Missing data patterns (univariate, monotone, arbitrary) are described as far as they are relevant for choosing an appropriate technique to compensate for missing
作者: 極端的正確性    時(shí)間: 2025-3-25 17:43

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作者: tendinitis    時(shí)間: 2025-3-26 08:54
2199-7357 ther quantitative researchers who analyze incompletely observed data sets, as well as master’s and PhD students with a sound basic knowledge of statistics.?.978-3-030-38166-0978-3-030-38164-6Series ISSN 2199-7357 Series E-ISSN 2199-7365
作者: coltish    時(shí)間: 2025-3-26 15:44
Textbook 2020erstanding of the procedures. This book is intended for social and health scientists and other quantitative researchers who analyze incompletely observed data sets, as well as master’s and PhD students with a sound basic knowledge of statistics.?.
作者: 江湖郎中    時(shí)間: 2025-3-26 20:42
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