Obtaining reliable and timely estimates of migration flows is critical for advancing the migration theory and guiding policy decisions, but it remains a challenge. Digital data provide granular information on time and space, but do not draw from representative samples of the population, leading to biased estimates. We propose a method for…

Propensity score analysis (PSA) is a methodological technique which may correct for selection bias in a quasi-experiment by modeling the selection process using observed covariates. Because logistic regression is well understood by researchers in a variety of fields and easy to implement in a number of popular software packages, it has…

The effects of variance heterogeneity on the empirical probability of a Type I error for the analysis of variance (ANOVA) F-test are examined. The rate of Type I error varies as a function of the degree of variance heterogeneity, and the ANOVA F-test is not always robust to variance heterogeneity when sample sizes are equal. (Author/JAC)

The statistician has n independent estimates of a parameter he knows is positive, but, as is the case in components-of-variance problems, some of the estimates may be negative. If the n estimates are to be combined into a single number, we compare the obvious rule, that of averaging the n values and taking the positive part of the result, with…

See EJ 030 376 and also TM 500 284 in this issue. (CK)

When random assignment has been accomplished and an analysis of covariance (ANCOVA) is being used to correct for initial differences among treatment groups, use of unreliable covariables not only decreases the power of ANCOVA, but also causes ANCOVA to test biased treatment effects. Several correction procedures have been suggested for the single…

Causal models often omit variables that should be included, use variables that are measured fallibly, and ignore time lags. Such practices can lead to severely biased estimates of effects. The discussion explains these biases and shows how to take them into account. (Author)

The methods used by Humphreys and Dachler to estimate effects in their analysis of Project TALENT data to test Jensen's Theory of Intelligence are shown to produce biased estimates. (Author/TA)

In large-scale surveys, it is no longer uncommon for repeated measurements to be obtained from respondents and analyses performed to gauge the magnitiude of nonsampling errors. This is particularly true for periodic surveys and longitudinal surveys where a very large investment in data collection is made. This technical note, aimed at the analysis…

Fairness or unfairness may be an attribute of a test per se, or of its use, or of its statistical treatment. An hypothetical situation designed to be intrinsically fair and unbiased is used to show that analysis of covariance as a statistical method may introduce bias to the treatment of test scores. In contrast, equipercentile equating methods…

Single administration (beta-binomial) estimates for the raw agreement index p and the corrected-for-chance kappa index in mastery testing are compared with those based on two test administrations in terms of estimation bias and sampling variability. Bias is about 2.5 percent for p and 10 percent for kappa. (Author/RL)

A general model is described which can be used to represent the four common types of meta-analysis: (1) estimation of effect size by combining study outcomes; (2) estimation of effect size by contrasting study outcomes; (3) estimation of statistical significance by combining study outcomes; and (4) estimation of statistical significance by…

Simplicity and flexibility of the full rank linear model motivated this paper which introduces researchers to the theory necessary to understand the model and apply the theory in the analysis of some standard fixed effects experimental designs. The theory and examples should help researchers use the model as an experimental tool and a model for…

Four techniques for assessing differences between least-squares estimators of regression coefficients from group and individual-level data are summarized. The utility and suitability of all four approaches are discussed when (1) data are grouped by a nominal characteristic; (2) there are multiple regressors; or (3) individual-level data cannot be…

Path analysis was used to reevaluate the analysis of covariance quasiexperimental study of the effectiveness of the Head Start program. Contrary to the original analysis, the alternative approach yields small positive estimates of effect. (Author/CTM)