Bayesian perspectives for epidemiologic research. III. Bias analysis via missing-data methods

نویسندگان

چکیده

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Bayesian perspectives for epidemiologic research: III. Bias analysis via missing-data methods.

I present some extensions of Bayesian methods to situations in which biases are of concern. First, a basic misclassification problem is illustrated using data from a study of sudden infant death syndrome. Bayesian analyses are then given. These analyses can be conducted directly, or by converting actual-data records to incomplete records and prior distributions to complete-data records, then ap...

متن کامل

Performance evaluation of different estimation methods for missing rainfall data

There are numerous methods to estimate missing values of which some are used depending on the data type and regional climatic characteristics. In this research, part of the monthly precipitation data in Sarab synoptic station, east Azerbaijan province, Iran was randomly considered missing values. In order to study the effectiveness of various methods to estimate missing data, by seven classic s...

متن کامل

Bayesian Multiple Imputation and Maximum Likelihood Methods for Missing Data

Bayesian multiple imputation and maximum likelihood provide useful strategy for dealing with dataset including missing values. Imputation methods affect the significance of test results and the quality of estimates. In this paper, the general procedures of multiple imputation and maximum likelihood described which include the normal-based analysis of a multiple imputed dataset. A Monte Carlo si...

متن کامل

Bayesian perspectives for epidemiological research: I. Foundations and basic methods.

One misconception (of many) about Bayesian analyses is that prior distributions introduce assumptions that are more questionable than assumptions made by frequentist methods; yet the assumptions in priors can be more reasonable than the assumptions implicit in standard frequentist models. Another misconception is that Bayesian methods are computationally difficult and require special software. ...

متن کامل

Choosing Appropriate Methods for Missing Data in Medical Research: a Decision Algorithm on Methods for Missing Data

Missing data (MD) are a common problem in medical research. When ignored or treated not appropriately, MD can lead to seriously biased results. Currently, there are no comprehensive guidelines for efficiently identifying suitable imputation methods in different MD situations. The objective of the paper is to discuss various methods to handle missing data. Based on a selective literature search,...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: International Journal of Epidemiology

سال: 2010

ISSN: 0300-5771,1464-3685

DOI: 10.1093/ije/dyq113