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Showing 1 to 15 of 25 results Save | Export
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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
Feller, Avi; Greif, Evan; Ho, Nhat; Miratrix, Luke; Pillai, Natesh – Grantee Submission, 2019
Principal stratification is a widely used framework for addressing post-randomization complications. After using principal stratification to define causal effects of interest, researchers are increasingly turning to finite mixture models to estimate these quantities. Unfortunately, standard estimators of mixture parameters, like the MLE, are known…
Descriptors: Statistical Analysis, Maximum Likelihood Statistics, Models, Statistical Distributions
Yongyun Shin; Stephen W. Raudenbush – Grantee Submission, 2023
We consider two-level models where a continuous response R and continuous covariates C are assumed missing at random. Inferences based on maximum likelihood or Bayes are routinely made by estimating their joint normal distribution from observed data R[subscript obs] and C[subscript obs]. However, if the model for R given C includes random…
Descriptors: Maximum Likelihood Statistics, Hierarchical Linear Modeling, Error of Measurement, Statistical Distributions
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Deke, John; Finucane, Mariel; Thal, Daniel – National Center for Education Evaluation and Regional Assistance, 2022
BASIE is a framework for interpreting impact estimates from evaluations. It is an alternative to null hypothesis significance testing. This guide walks researchers through the key steps of applying BASIE, including selecting prior evidence, reporting impact estimates, interpreting impact estimates, and conducting sensitivity analyses. The guide…
Descriptors: Bayesian Statistics, Educational Research, Data Interpretation, Hypothesis Testing
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Cai, Tianji; Xia, Yiwei; Zhou, Yisu – Sociological Methods & Research, 2021
Analysts of discrete data often face the challenge of managing the tendency of inflation on certain values. When treated improperly, such phenomenon may lead to biased estimates and incorrect inferences. This study extends the existing literature on single-value inflated models and develops a general framework to handle variables with more than…
Descriptors: Statistical Distributions, Probability, Statistical Analysis, Statistical Bias
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Ranger, Jochen; Kuhn, Jörg Tobias; Ortner, Tuulia M. – Educational and Psychological Measurement, 2020
The hierarchical model of van der Linden is the most popular model for responses and response times in tests. It is composed of two separate submodels--one for the responses and one for the response times--that are joined at a higher level. The submodel for the response times is based on the lognormal distribution. The lognormal distribution is a…
Descriptors: Reaction Time, Tests, Statistical Distributions, Models
Ding, Peng; Dasgupta, Tirthankar – Grantee Submission, 2017
Fisher randomization tests for Neyman's null hypothesis of no average treatment effects are considered in a finite population setting associated with completely randomized experiments with more than two treatments. The consequences of using the F statistic to conduct such a test are examined both theoretically and computationally, and it is argued…
Descriptors: Statistical Analysis, Statistical Inference, Causal Models, Error Patterns
Cain, Meghan K.; Zhang, Zhiyong; Yuan, Ke-Hai – Grantee Submission, 2017
Nonnormality of univariate data has been extensively examined previously (Blanca et al., 2013; Micceri, 1989). However, less is known of the potential nonnormality of multivariate data although multivariate analysis is commonly used in psychological and educational research. Using univariate and multivariate skewness and kurtosis as measures of…
Descriptors: Multivariate Analysis, Probability, Statistical Distributions, Psychological Studies
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Kang, Yoonjeong; Harring, Jeffrey R.; Li, Ming – Journal of Experimental Education, 2015
The authors performed a Monte Carlo simulation to empirically investigate the robustness and power of 4 methods in testing mean differences for 2 independent groups under conditions in which 2 populations may not demonstrate the same pattern of nonnormality. The approaches considered were the t test, Wilcoxon rank-sum test, Welch-James test with…
Descriptors: Comparative Analysis, Monte Carlo Methods, Statistical Analysis, Robustness (Statistics)
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Noll, Jennifer; Hancock, Stacey – Educational Studies in Mathematics, 2015
This research investigates what students' use of statistical language can tell us about their conceptions of distribution and sampling in relation to informal inference. Prior research documents students' challenges in understanding ideas of distribution and sampling as tools for making informal statistical inferences. We know that these…
Descriptors: Statistical Analysis, Mathematics Instruction, Mathematical Concepts, Inferences
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Bishara, Anthony J.; Hittner, James B. – Educational and Psychological Measurement, 2015
It is more common for educational and psychological data to be nonnormal than to be approximately normal. This tendency may lead to bias and error in point estimates of the Pearson correlation coefficient. In a series of Monte Carlo simulations, the Pearson correlation was examined under conditions of normal and nonnormal data, and it was compared…
Descriptors: Research Methodology, Monte Carlo Methods, Correlation, Simulation
Imbens, Guido W.; Rubin, Donald B. – Cambridge University Press, 2015
Most questions in social and biomedical sciences are causal in nature: what would happen to individuals, or to groups, if part of their environment were changed? In this groundbreaking text, two world-renowned experts present statistical methods for studying such questions. This book starts with the notion of potential outcomes, each corresponding…
Descriptors: Causal Models, Statistical Inference, Statistics, Social Sciences
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Schweig, Jonathan – Journal of Educational and Behavioral Statistics, 2014
Measures of classroom environments have become central to policy efforts that assess school and teacher quality. This has sparked a wide interest in using multilevel factor analysis to test measurement hypotheses about classroom-level variables. One approach partitions the total covariance matrix and tests models separately on the…
Descriptors: Factor Analysis, Robustness (Statistics), Measurement, Classroom Environment
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Akani, Omiko – Journal of Education and Practice, 2015
This study investigated the levels of possession of science process skills by final year Nigerian Certificate in Education (NCE) Students in colleges of Education in South-Eastern States of Nigeria. The skills that were assessed were observation, experimentation, measurement, communication, and inference. The research was guided by five research…
Descriptors: Foreign Countries, Science Process Skills, College Students, Likert Scales
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Padilla, Miguel A.; Divers, Jasmin – Educational and Psychological Measurement, 2013
The performance of the normal theory bootstrap (NTB), the percentile bootstrap (PB), and the bias-corrected and accelerated (BCa) bootstrap confidence intervals (CIs) for coefficient omega was assessed through a Monte Carlo simulation under conditions not previously investigated. Of particular interests were nonnormal Likert-type and binary items.…
Descriptors: Sampling, Statistical Inference, Computation, Statistical Analysis
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