Statistical procedures for missing data have vastly improved, yet misconception and unsound practice still abound. The authors frame the missing-data problem, review methods, offer advice, and raise issues that remain unresolved. They clear up common misunderstandings regarding the missing at random (MAR) concept. They summarize the evidence against older procedures and, with few exceptions, discourage their use. They present, in both technical and practical language, 2 general approaches that come highly recommended: maximum likelihood (ML) and Bayesian multiple imputation (MI). Newer developments are discussed, including some for dealing with missing data that are not MAR. Although not yet in the mainstream, these procedures may eventually extend the ML and MI methods that currently represent the state of the art.

/pdf/missing-data-our-view-of-the-state-of-the-art-3xnwc88wmd.pdf

Missing data: Our view of the state of the art.

Cross-sectional data from the Medical Outcomes Study (MOS) were analyzed to test the validity of the MOS 36-Item Short-Form Health Survey (SF-36) scales as measures of physical and mental health constructs. Results from traditional psychometric and clinical tests of validity were compared. Principal

The MOS 36-Item Short-Form Health Survey (SF-36): II. Psychometric and clinical tests of validity in measuring physical and mental health constructs.

Background In patients with high cholesterol levels, lowering the cholesterol level reduces the risk of coronary events, but the effect of lowering cholesterol levels in the majority of patients with coronary disease, who have average levels, is less clear. Methods In a double-blind trial lasting five years, we administered either 40 mg of pravastatin per day or placebo to 4159 patients (3583 men and 576 women) with myocardial infarction who had plasma total cholesterol levels below 240 mg per deciliter (mean, 209) and low-density lipoprotein (LDL) cholesterol levels of 115 to 174 mg per deciliter (mean, 139). The primary end point was a fatal coronary event or a nonfatal myocardial infarction. Results The frequency of the primary end point was 10.2 percent in the pravastatin group and 13.2 percent in the placebo group, an absolute difference of 3 percentage points and a 24 percent reduction in risk (95 percent confidence interval, 9 to 36 percent; P = 0.003). Coronary bypass surgery was needed in 7.5 per...

The Effect of Pravastatin on Coronary Events after Myocardial Infarction in Patients with Average Cholesterol Levels

Quantification of coronary artery calcium using ultrafast computed tomography

A common concern when faced with multivariate data with missing values is whether the missing data are missing completely at random (MCAR); that is, whether missingness depends on the variables in the data set. One way of assessing this is to compare the means of recorded values of each variable between groups defined by whether other variables in the data set are missing or not. Although informative, this procedure yields potentially many correlated statistics for testing MCAR, resulting in multiple-comparison problems. This article proposes a single global test statistic for MCAR that uses all of the available data. The asymptotic null distribution is given, and the small-sample null distribution is derived for multivariate normal data with a monotone pattern of missing data. The test reduces to a standard t test when the data are bivariate with missing data confined to a single variable. A limited simulation study of empirical sizes for the test applied to normal and nonnormal data suggests th...

https://www.jstor.org/stable/pdfplus/2290157.pdf

A Test of Missing Completely at Random for Multivariate Data with Missing Values

Introduction to statistical analysis , Introduction to statistical analysis , مرکز فناوری اطلاعات و اطلاع رسانی کشاورزی

Introduction to Statistical Analysis

BMDP statistical software

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The standard method of dealing with sensitivity of dosage-mortality data is the probit technique developed by Bliss and Fisher. This paper provides an alternative technique based on a special system for obtaining such data. It has some advantages when observations must be taken on individuals rather than groups of individuals, and it may be preferred in certain other situations. * This paper is in part an adaptation of a memorandum submitted to the Applied Mathematics Panel by the Statistical Research Group, Princeton University. The Statistical Research Group operated under a contract with the Office of Scientific Research and Development, and was directed by the Applied Mathematics Panel of the National Defense Research Committee.

https://www.jstor.org/stable/info/2280071

A Method for Obtaining and Analyzing Sensitivity Data

http://depa.fquim.unam.mx/amyd/archivero/ac1951_23_636_13353.pdf

Wilfrid J. Dixon

Papers

Introduction to Statistical Analysis

BMDP statistical software

BMD : biomedical computer programs

A Method for Obtaining and Analyzing Sensitivity Data

Simplified Statistics for Small Numbers of Observations