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Ting Dai; Yang Du; Jennifer Cromley; Tia Fechter; Frank Nelson – Journal of Experimental Education, 2024
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…
Descriptors: Research Problems, Research Design, Data, Matrices
Mthuli, Syanda Alpheous; Ruffin, Fayth; Singh, Nikita – International Journal of Social Research Methodology, 2022
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…
Descriptors: Qualitative Research, Sample Size, Sampling, Research Problems
Sim, Julius; Saunders, Benjamin; Waterfield, Jackie; Kingstone, Tom – International Journal of Social Research Methodology, 2018
There has been considerable recent interest in methods of determining sample size for qualitative research a priori, rather than through an adaptive approach such as saturation. Extending previous literature in this area, we identify four distinct approaches to determining sample size in this way: rules of thumb, conceptual models, numerical…
Descriptors: Sample Size, Qualitative Research, Research Methodology, Statistical Analysis
Sim, Julius; Saunders, Benjamin; Waterfield, Jackie; Kingstone, Tom – International Journal of Social Research Methodology, 2018
In his detailed response to our paper on sample size in qualitative research, Norman Blaikie raises important issues concerning conceptual definitions and taxonomy. In particular, he points out the problems associated with a loose, generic application of adjectives such as 'qualitative' or 'inductive'. We endorse this concern, though we suggest…
Descriptors: Sample Size, Sampling, Qualitative Research, Research Methodology
Contandriopoulos, Damien; Sapeha, Halina; Larouche, Catherine – International Journal of Social Research Methodology, 2019
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…
Descriptors: Social Networks, Network Analysis, Data Collection, Research Problems
McNeish, Daniel – Journal of Experimental Education, 2018
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…
Descriptors: Growth Models, Sampling, Sample Size, Hierarchical Linear Modeling
Soysal, Sümeyra; Arikan, Çigdem Akin; Inal, Hatice – Online Submission, 2016
This study aims to investigate the effect of methods to deal with missing data on item difficulty estimations under different test length conditions and sampling sizes. In this line, a data set including 10, 20 and 40 items with 100 and 5000 sampling size was prepared. Deletion process was applied at the rates of 5%, 10% and 20% under conditions…
Descriptors: Research Problems, Data Analysis, Item Response Theory, Test Items
McNeish, Daniel – Review of Educational Research, 2017
In education research, small samples are common because of financial limitations, logistical challenges, or exploratory studies. With small samples, statistical principles on which researchers rely do not hold, leading to trust issues with model estimates and possible replication issues when scaling up. Researchers are generally aware of such…
Descriptors: Models, Statistical Analysis, Sampling, Sample Size
Lai, Mark H. C.; Kwok, Oi-man – Journal of Experimental Education, 2015
Educational researchers commonly use the rule of thumb of "design effect smaller than 2" as the justification of not accounting for the multilevel or clustered structure in their data. The rule, however, has not yet been systematically studied in previous research. In the present study, we generated data from three different models…
Descriptors: Educational Research, Research Design, Cluster Grouping, Statistical Data
Ritter, Lois A., Ed.; Sue, Valerie M., Ed. – New Directions for Evaluation, 2007
This chapter provides an overview of sampling methods that are appropriate for conducting online surveys. The authors review some of the basic concepts relevant to online survey sampling, present some probability and nonprobability techniques for selecting a sample, and briefly discuss sample size determination and nonresponse bias. Although some…
Descriptors: Sampling, Probability, Evaluation Methods, Computer Assisted Testing
Onwuegbuzie, Anthony J.; Collins, Kathleen M. T. – Qualitative Report, 2007
This paper provides a framework for developing sampling designs in mixed methods research. First, we present sampling schemes that have been associated with quantitative and qualitative research. Second, we discuss sample size considerations and provide sample size recommendations for each of the major research designs for quantitative and…
Descriptors: Social Science Research, Qualitative Research, Methods Research, Sample Size
Linked Pairs of Bereaved Persons: A Method for Increasing the Sample Size in a Study of Bereavement.

Murphy, Shirley A.; Stewart, Barbara J. – Omega: Journal of Death and Dying, 1986
Describes a sampling strategy which involves linked pairs of persons used to obtain bereaved respondents for a study examining loss and coping responses following a recent natural disaster. The sampling procedure appeared not to produce an obvious bias and was very beneficial in meeting the research objectives. (Author/NRB)
Descriptors: Bereavement, Coping, Death, Research Problems

Hiller, Dana V.; Philliber, William W. – Journal of Marriage and the Family, 1985
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.…
Descriptors: Generalization, Influences, Research Problems, Sample Size

McGraw, Kenneth O.; And Others – Journal of Consulting and Clinical Psychology, 1994
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…
Descriptors: Measurement Techniques, Monte Carlo Methods, Research Methodology, Research Problems

Flack, Virginia F.; And Others – Psychometrika, 1988
A method is presented for determining sample size that will achieve a pre-specified bound on confidence interval width for the interrater agreement measure "kappa." The same results can be used when a pre-specified power is desired for testing hypotheses about the value of kappa. (Author/SLD)
Descriptors: Evaluation Methods, Interrater Reliability, Research Methodology, Research Problems