How Long to Read Bayesian Nonparametrics for Causal Inference and Missing Data

How Long Does it Take to Read Bayesian Nonparametrics for Causal Inference and Missing Data?

It takes the average reader 4 hours and 26 minutes to read Bayesian Nonparametrics for Causal Inference and Missing Data by Michael J. Daniels

Assuming a reading speed of 250 words per minute. Learn more

Description

Bayesian Nonparametrics for Causal Inference and Missing Data provides an overview of flexible Bayesian nonparametric (BNP) methods for modeling joint or conditional distributions and functional relationships, and their interplay with causal inference and missing data. This book emphasizes the importance of making untestable assumptions to identify estimands of interest, such as missing at random assumption for missing data and unconfoundedness for causal inference in observational studies. Unlike parametric methods, the BNP approach can account for possible violations of assumptions and minimize concerns about model misspecification. The overall strategy is to first specify BNP models for observed data and then to specify additional uncheckable assumptions to identify estimands of interest. The book is divided into three parts. Part I develops the key concepts in causal inference and missing data and reviews relevant concepts in Bayesian inference. Part II introduces the fundamental BNP tools required to address causal inference and missing data problems. Part III shows how the BNP approach can be applied in a variety of case studies. The datasets in the case studies come from electronic health records data, survey data, cohort studies, and randomized clinical trials. Features • Thorough discussion of both BNP and its interplay with causal inference and missing data • How to use BNP and g-computation for causal inference and non-ignorable missingness • How to derive and calibrate sensitivity parameters to assess sensitivity to deviations from uncheckable causal and/or missingness assumptions • Detailed case studies illustrating the application of BNP methods to causal inference and missing data • R code and/or packages to implement BNP in causal inference and missing data problems The book is primarily aimed at researchers and graduate students from statistics and biostatistics. It will also serve as a useful practical reference for mathematically sophisticated epidemiologists and medical researchers.

How long is Bayesian Nonparametrics for Causal Inference and Missing Data?

Bayesian Nonparametrics for Causal Inference and Missing Data by Michael J. Daniels is 263 pages long, and a total of 66,539 words.

This makes it 89% the length of the average book. It also has 81% more words than the average book.

How Long Does it Take to Read Bayesian Nonparametrics for Causal Inference and Missing Data Aloud?

The average oral reading speed is 183 words per minute. This means it takes 6 hours and 3 minutes to read Bayesian Nonparametrics for Causal Inference and Missing Data aloud.

What Reading Level is Bayesian Nonparametrics for Causal Inference and Missing Data?

Bayesian Nonparametrics for Causal Inference and Missing Data is suitable for students ages 12 and up.

Note that there may be other factors that effect this rating besides length that are not factored in on this page. This may include things like complex language or sensitive topics not suitable for students of certain ages.

When deciding what to show young students always use your best judgement and consult a professional.

Where Can I Buy Bayesian Nonparametrics for Causal Inference and Missing Data?

Bayesian Nonparametrics for Causal Inference and Missing Data by Michael J. Daniels is sold by several retailers and bookshops. However, Read Time works with Amazon to provide an easier way to purchase books.

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