This study examined the relationship between data use and achievement at 13 urban Title I schools. Using multiple methods, including test scores, district surveys, school transformation plans, and four case study site visits, the researchers found wide variation in the use of data to inform instruction and planning. In some cases, schools were …

Two-stage sampling procedures for comparing two population means when variances are heterogeneous have been developed by D. G. Chapman (1950) and B. K. Ghosh (1975). Both procedures assume sampling from populations that are normally distributed. The present study reports on the effect that sampling from non-normal distributions has on Type I error…

The relationship of sample size to number of variables in the use of factor analysis has been treated by many investigators. In attempting to explore what the minimum sample size should be, none of these investigators pointed out the constraints imposed on the dimensionality of the variables by using a sample size smaller than the number of…

Scores on the multiple-choice sections of alternate forms are equated through anchor-test equating for the Advanced Placement Program (AP) examinations. There is no linkage of free-response sections since different free-response items are given yearly. However, the free-response and multiple-choice sections are combined to produce a composite.…

It is erroneous to extend or generalize the inter-rater reliability coefficient estimated from only a (small) proportion of the sample to the rest of the sample data where only one rater is used for scoring, although such generalization is often made implicitly in practice. It is shown that if inter-rater reliability estimate from part of a sample…

After reviewing the multiple fit indices in structural equation models, evidence on their behavior is presented through simulation studies in which sample size, estimation method, and model misspecification varied. Two sampling studies, with and without known populations, are presented, and implications for the use of fit indices are discussed.…

Describes the use of critical multiplism to evaluate the advantages and disadvantages of random sampling and deliberate sampling for heterogeneity. Suggests a model for using deliberate sampling for heterogeneity when the population parameters are unknown. Applies this model to a study of the psychosocial rehabilitation workforce. (SLD)

Sampling error refers to variability that is unique to the sample. If the sample is the entire population, then there is no sampling error. A related point is that sampling error is a function of sample size, as a hypothetical example illustrates. As the sample statistics more and more closely approximate the population parameters, the sampling…

This paper explains the underlying assumptions of the sampling distribution and its role in significance testing. To compute statistical significance, estimates of population parameters must be obtained so that only one sampling distribution is defined. A sampling distribution is the underlying distribution of a statistic. Sampling distributions…

A review of articles that report study results based on couple samples indicated response rates are rarely high enough for statistical inference. Four procedures that can be used to compensate for insufficient response rates (collecting information from nonparticipants, census comparisons, adjustment in analysis, and replication) are examined.…

A Monte Carlo study involving 1,000 random samples from each of 64 different population matrices investigated bias in both canonical correlation and redundancy coefficients. Results indicate that the Wherry correction provides a reasonable solution to this problem and that canonical results are not as biased as has been believed. (TJH)

Suggest practical procedure for estimating number of subjects that need to be screened to obtain sample of fixed size that meets multiple correlated criteria. Procedure described is based on fact that least-squares regression provides good quadratic fit for Monte Carlo estimates of multivariate probabilities when they are plotted as function of…

Presents an experiment on the sampling process including sample size and particle size. (YDS)

Statistical significance is often misinterpreted to mean replicability or generalizability of results, although a statistically significant difference does not equal a reliable difference. Sample splitting procedures may be a more accurate way of estimating research result generalizability. This type of cross-validation involves randomly dividing…

This paper discusses the impact of sampling error on the construction of confidence intervals around effect sizes. Sampling error affects the location and precision of confidence intervals. Meta-analytic resampling demonstrates that confidence intervals can haphazardly bounce around the true population parameter. Special software with graphical…