The data we encounter in real life often contain missing values. In sampling methods, missing value imputation is done with different methods. This article proposes novel logarithmic type imputation methods for estimating the population mean in the presence of missing data under ranked set sampling (RSS). According to the determined theoretical…

Address-based sampling (ABS) refers to the use a list of addresses derived from the U.S. Postal Service's Computerized Delivery Sequence File as a sampling frame. While most residential addresses are included on an ABS frame, it still suffers from undercoverage. Undercoverage is problematic only if the uncovered units have different attributes…

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…

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…

The various empirical models built for enrollment management, operations, and program evaluation purposes may have lost their predictive power as a result of the recent collective impact of COVID restrictions, widespread social upheaval, and the shift in educational preferences. This statistical artifact is known as model drifting, data-shift,…

Meta-studies are often conducted on empirical findings obtained from overlapping samples. Sample overlap is common in research fields that strongly rely on aggregated observational data (eg, economics and finance), where the same set of data may be used in several studies. More generally, sample overlap tends to occur whenever multiple estimates…

Since 2018, colleagues from two research centers at Dublin City University have been collaborating to develop a measurement scale to assess individuals' ability to identify workplace bullying. Having agreed on an operational definition of the construct, an item pool of 26 workplace bullying scenarios, that is, short descriptions of…

This study examined caregivers' longitudinal reports of adolescent multiracial categorization across the ages of 9.5, 10.5, and 14 years, and adolescents' reports of their own multiracial categorization at the age of 14 years. A portion of caregivers' reports of adolescent multiracial status were inconsistent across the years of the study; some…

Factorial surveys use a population of vignettes to elicit respondents' attitudes or beliefs about different hypothetical scenarios. However, the vignette population is frequently too large to be assessed by each respondent. Experimental designs such as randomized block confounded factorial (RBCF) designs, D-optimal designs, or random sampling…

Traditional observed variable multilevel models for evaluating indirect effects are limited by their inability to quantify measurement and sampling error. They are further restricted by being unable to fully separate within- and between-level effects without bias. Doubly latent models reduce these biases by decomposing the observed within-level…

Recruiting participants through gatekeepers has been widely discussed in qualitative research. However, when a sampling frame is not available, surveying through gatekeepers can also be important for quantitative studies. We used three sampling methods to survey guardians of University students: (a) a gatekeeper variant of the time-space sampling,…

As a result of the evidence-based decision-making movement, the number of randomized trials evaluating educational programs and curricula has increased dramatically over the past 20 years. Policy makers and practitioners are encouraged to use the results of these trials to inform their decision making in schools and school districts. At the same…

In the field of social sciences, certain tasks, such as the identification of typologies and the characterization of groups of individuals according to a set of questions, tend to pose a challenge for researchers. Further complications arise if the chosen rating scale is from 0 to 10, since the responses can be treated either as metric or…

This research note discusses opportunities and challenges of using online survey engines for social network analysis (SNA) data collection and assessing sample size and representativeness. The discussion is based on a case study of SNA data collection for a pilot research on health-relevant policy networks in Canada. Our approach demonstrates how…

Small samples are common in growth models due to financial and logistical difficulties of following people longitudinally. For similar reasons, longitudinal studies often contain missing data. Though full information maximum likelihood (FIML) is popular to accommodate missing data, the limited number of studies in this area have found that FIML…