Are values missing randomly in survey research?

From: Educational Research Quarterly | Date: March 1, 2000| Author: | Copyright information

Many missing data studies have simulated data, randomly deleted values, and investigated which method of handling the missing values would most closely approximate the original data. Regression procedures have emerged as the most recommended methods. If the values are missing randomly, these procedures are effective. If, however, the values are not missing randomly, the use of regression procedures to impute values for missing data is questionable. The purpose of this study was to determine if values were missing randomly in samples selected from the student cohort of the National Education ...

Read all of this article with a FREE trial to HighBeam Research

Related newspaper, magazine, and trade journal articles from HighBeam Research

(Including press releases, facts, information, and biographies)

Inference With Imputed Conditional Means.(Statistical Data Included)
; ...technique for handling missing data in a large dataset...available to model the missing values than those who...approaches is that missing-data uncertainty is...versions of the missing values. In this article...multivariate, but with missing values on just ...
Managing missing data.(Data Systems)
; ...there are no missing values in the data...main effect of missing values in a database...problem of missing data. In the worst...desirable that the missing values be replaced...imputing the missing values to convert...database to be missing. The huge ...
Biases in SPSS 12.0 Missing Value Analysis.(Product/Service Evaluation)
; ...dataset has missing values, the difficulty...observed and missing values, then values...and not on missing values), then values...observed nor on missing values, then values...can ignore the missing data mechanism provided...MAR, then the missing ...
Missing-data methods for generalized linear models: a comparative review.
; ...every subject. Missing data may arise due...the problem of missing data is to analyze...commonly used with missing values in the covariates...that handle missing data more appropriately...GLMs) with missing covariate data...variables with missing ...
Imputing missing data: a comparison of methods for social work researchers.(management)
; ...method to handle missing data during analyses...researchers. Often, missing values are just ignored...used to replace missing data from two data...sets, each with missing values. The results effectively...the amount of missing data or how ...
Multiple imputation after 18+ years.
; ...DESIGNED TO ADDRESS Missing values are a problem in many...addressing problems due to missing values: alternative methods...objectives for handling missing data in this environment...in the presence of missing data under particular...use data sets have missing ...
Computational strategies for multivariate linear mixed-effects models with missing values.
; ...clustered data with missing values. Current methodology...imbalance or missing data in a single...cannot handle missing values in multiple...random effects as missing data, but integrates...datasets with missing values. Let [y.sub...
Multiple imputation for incomplete data with semicontinuous variables.
; ...Semicontinuous Variables Missing data often complicate...handling such missing data is to impute...data with all missing values imputed) is generated...there were no missing data. Usually, the...caused by the missing data from the...data with no ...
Missing Data: A Gentle Introduction
; ...Sidani, and Aurelio Jose Figueredo. Missing Data: A Gentle Introduction. New York: Guilford...incomplete data-and despite the ubiquity of missing data in social research-the preponderance...journal articles still essentially ignores missing data altogether. Continued reliance upon...
Using PPCA to Estimate EOFs in the Presence of Missing Values
; ...be carried out easily when there are missing values within the dataset. One possible solution...with data randomly removed to simulate missing values, and then reconstructs the data using...than calculated. The replacement of missing values was also computationally more efficient...