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Cheng, Siwei – Sociological Methods & Research, 2023
One of the most important developments in the current era of social sciences is the growing availability and diversity of data, big and small. Social scientists increasingly combine information from multiple data sets in their research. While conducting statistical analyses with linked data is relatively straightforward, borrowing information…
Descriptors: Social Science Research, Statistical Analysis, Statistical Distributions, Statistical Bias
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Spit, Sybren; Andringa, Sible; Rispens, Judith; Aboh, Enoch O. – Journal of Psycholinguistic Research, 2022
Many studies demonstrate that detecting statistical regularities in linguistic input plays a key role in language acquisition. Yet, it is unclear to what extent statistical learning is involved in more naturalistic settings, when young children have to acquire meaningful grammatical elements. In the present study, we address these points, by…
Descriptors: Kindergarten, Grammar, Statistical Analysis, Statistical Distributions
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Man, Kaiwen; Schumacker, Randall; Morell, Monica; Wang, Yurou – Educational and Psychological Measurement, 2022
While hierarchical linear modeling is often used in social science research, the assumption of normally distributed residuals at the individual and cluster levels can be violated in empirical data. Previous studies have focused on the effects of nonnormality at either lower or higher level(s) separately. However, the violation of the normality…
Descriptors: Hierarchical Linear Modeling, Statistical Distributions, Statistical Bias, Computation
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Migliavaca, Celina Borges; Stein, Cinara; Colpani, Verônica; Barker, Timothy Hugh; Ziegelmann, Patricia Klarmann; Munn, Zachary; Falavigna, Maicon – Research Synthesis Methods, 2022
Over the last decade, there has been a 10-fold increase in the number of published systematic reviews of prevalence. In meta-analyses of prevalence, the summary estimate represents an average prevalence from included studies. This estimate is truly informative only if there is no substantial heterogeneity among the different contexts being pooled.…
Descriptors: Incidence, Meta Analysis, Statistics, Statistical Distributions
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Cao, Wenhao; Siegel, Lianne; Zhou, Jincheng; Zhu, Motao; Tong, Tiejun; Chen, Yong; Chu, Haitao – Research Synthesis Methods, 2021
A reference interval provides a basis for physicians to determine whether a measurement is typical of a healthy individual. It can be interpreted as a prediction interval for a new individual from the overall population. However, a reference interval based on a single study may not be representative of the broader population. Meta-analysis can…
Descriptors: Meta Analysis, Statistical Analysis, Intervals, Computation
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Julia-Kim Walther; Martin Hecht; Benjamin Nagengast; Steffen Zitzmann – Structural Equation Modeling: A Multidisciplinary Journal, 2024
A two-level data set can be structured in either long format (LF) or wide format (WF), and both have corresponding SEM approaches for estimating multilevel models. Intuitively, one might expect these approaches to perform similarly. However, the two data formats yield data matrices with different numbers of columns and rows, and their "cols :…
Descriptors: Data, Monte Carlo Methods, Statistical Distributions, Matrices
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Guastadisegni, Lucia; Cagnone, Silvia; Moustaki, Irini; Vasdekis, Vassilis – Educational and Psychological Measurement, 2022
This article studies the Type I error, false positive rates, and power of four versions of the Lagrange multiplier test to detect measurement noninvariance in item response theory (IRT) models for binary data under model misspecification. The tests considered are the Lagrange multiplier test computed with the Hessian and cross-product approach,…
Descriptors: Measurement, Statistical Analysis, Item Response Theory, Test Items
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Frömke, Cornelia; Kirstein, Mathia; Zapf, Antonia – Research Synthesis Methods, 2022
The accuracy of a diagnostic test is often expressed using a pair of measures: sensitivity (proportion of test positives among all individuals with target condition) and specificity (proportion of test negatives among all individuals without target condition). If the outcome of a diagnostic test is binary, results from different studies can easily…
Descriptors: Accuracy, Diagnostic Tests, Meta Analysis, Statistical Analysis
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Riley, Richard D.; Collins, Gary S.; Hattle, Miriam; Whittle, Rebecca; Ensor, Joie – Research Synthesis Methods, 2023
Before embarking on an individual participant data meta-analysis (IPDMA) project, researchers should consider the power of their planned IPDMA conditional on the studies promising their IPD and their characteristics. Such power estimates help inform whether the IPDMA project is worth the time and funding investment, before IPD are collected. Here,…
Descriptors: Computation, Meta Analysis, Participant Characteristics, Data
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Daniel Seddig – Structural Equation Modeling: A Multidisciplinary Journal, 2024
The latent growth model (LGM) is a popular tool in the social and behavioral sciences to study development processes of continuous and discrete outcome variables. A special case are frequency measurements of behaviors or events, such as doctor visits per month or crimes committed per year. Probability distributions for such outcomes include the…
Descriptors: Growth Models, Statistical Analysis, Structural Equation Models, Crime
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Hollenbach, Florian M.; Bojinov, Iavor; Minhas, Shahryar; Metternich, Nils W.; Ward, Michael D.; Volfovsky, Alexander – Sociological Methods & Research, 2021
Missing observations are pervasive throughout empirical research, especially in the social sciences. Despite multiple approaches to dealing adequately with missing data, many scholars still fail to address this vital issue. In this article, we present a simple-to-use method for generating multiple imputations (MIs) using a Gaussian copula. The…
Descriptors: Data, Statistical Analysis, Statistical Distributions, Computation
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Orcan, Fatih – International Journal of Assessment Tools in Education, 2020
Checking the normality assumption is necessary to decide whether a parametric or non-parametric test needs to be used. Different ways are suggested in literature to use for checking normality. Skewness and kurtosis values are one of them. However, there is no consensus which values indicated a normal distribution. Therefore, the effects of…
Descriptors: Nonparametric Statistics, Statistical Analysis, Comparative Analysis, Statistical Distributions
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Elbers, Benjamin – Sociological Methods & Research, 2023
An important topic in the study of segregation are comparisons across space and time. This article extends current approaches in segregation measurement by presenting a five-term decomposition procedure that can be used to understand more clearly why segregation has changed or differs between two comparison points. Two of the five terms account…
Descriptors: Social Science Research, School Segregation, Equal Opportunities (Jobs), Residential Patterns
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Kulinskaya, Elena; Hoaglin, David C.; Bakbergenuly, Ilyas; Newman, Joseph – Research Synthesis Methods, 2021
The conventional Q statistic, using estimated inverse-variance (IV) weights, underlies a variety of problems in random-effects meta-analysis. In previous work on standardized mean difference and log-odds-ratio, we found superior performance with an estimator of the overall effect whose weights use only group-level sample sizes. The Q statistic…
Descriptors: Q Methodology, Meta Analysis, Statistical Analysis, Statistical Distributions
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Jasso, Guillermina – Sociological Methods & Research, 2021
Inequality often appears in linked pairs of variables. Examples include schooling and income, income and consumption, and wealth and happiness. Consider the famous words of Veblen: "wealth confers honor." Understanding inequality requires understanding input inequality, outcome inequality, and the relation between the two--in both…
Descriptors: Input Output Analysis, Justice, Research Methodology, Social Science Research
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