Given sample data, how do you calculate the value of a parameter? While this question is impossible to answer, it is frequently encountered in statistics classes when students are introduced to the distinction between a sample and a population (or between a statistic and a parameter). It is not uncommon for teachers of statistics to also confuse…

Parallel analysis has been considered one of the most accurate methods for determining the number of factors in factor analysis. One major advantage of parallel analysis over traditional factor retention methods (e.g., Kaiser's rule) is that it addresses the sampling variability of eigenvalues obtained from the identity matrix, representing the…

Latent class analysis (LCA) is a widely used technique for detecting unobserved population heterogeneity in cross-sectional data. Despite its popularity, the performance of LCA is not well understood. In this study, we evaluate the performance of LCA with binary data by examining classification accuracy, parameter estimation accuracy, and coverage…

This paper focuses on the considerations in determining the number of participants for qualitative research because of the lack of clear guidelines in this area. The study has employed a semi-systematic literature review that is embedded with the researcher's experience. The study has concluded that the purpose of the research, methodological…

Recent metascience suggests that motor behavior research may be underpowered, on average. Researchers can perform a priori power analyses to ensure adequately powered studies. However, there are common pitfalls that can result in underestimating the required sample size for a given design and effect size of interest. Critical evaluation of power…

Not knowing the population size is a common problem in data-limited contexts. Drawing on work in Sierra Leone, this short take outlines a four-step solution to this problem: (1) estimate the population size using expert interviews; (2) verify estimates using interviews with participants sampled; (3) triangulate using secondary data; and (4)…

Simple matrix sampling planned missing (SMS PD) design, introduce missing data patterns that lead to covariances between variables that are not jointly observed, and create difficulties for analyses other than mean and variance estimations. Based on prior research, we adopted a new multigroup confirmatory factor analysis (CFA) approach to handle…

Expected yield rates are essential to a survey's data collection plan, as they inform requisite sample sizes to meet the survey's objectives. Given an overall expected yield rate for a self-administered mail survey, this short take describes a simple method for using the Census Planning Database to assign differential yield rates to lower-level…

A central question in educational research is how classroom climate variables, such as teaching quality, goal structures, or interpersonal teacher behavior, are related to critical student outcomes, such as students' achievement and motivation. Student ratings are frequently used to measure classroom climate. When using student ratings to assess…

Practitioners and policymakers often want estimates of the effect of an intervention for their local community, e.g., region, state, county. In the ideal, these multiple population average treatment effect (ATE) estimates will be considered in the design of a single randomized trial. Methods for sample selection for generalizing the sample ATE to…

Qualitative research sample size determination has always been a contentious and confusing issue. Studies are often vague when explaining the processes and justifications that have been used to determine sample size and strategy. Some provide no mention of sampling at all, whilst others rely too heavily on the concept of saturation for determining…

Convenience sampling dominates social science research. But there is a paucity of studies comparing the impact of sample source type based on composite-based theoretical model relationships. This study empirically tests four different sample sources (e.g. student, crowdsourced, professional panel, and respondent driven social network) to assess…

For ease of instruction in the classroom, the one-way analysis of variance F statistic is rewritten in terms of pairwise differences in individual sample means instead of differences of individual sample means from the overall sample mean. Likewise, the Kruskal-Wallis statistic may be rewritten in terms of pairwise differences in individual…

We discuss analysis of 5-grade Likert type data in the two-sample case. Analysis using two-sample "t" tests, nonparametric Wilcoxon tests, and ordinal regression methods, are compared using simulated data based on an ordinal regression paradigm. One thousand pairs of samples of size "n"=10 and "n"=30 were generated,…

Over the past ten years, propensity score methods have made an important contribution to improving generalizations from studies that do not select samples randomly from a population of inference. However, these methods require assumptions and recent work has considered the role of bounding approaches that provide a range of treatment impact…