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Tenko Raykov; Christine DiStefano; Lisa Calvocoressi – Educational and Psychological Measurement, 2024
This note demonstrates that the widely used Bayesian Information Criterion (BIC) need not be generally viewed as a routinely dependable index for model selection when the bifactor and second-order factor models are examined as rival means for data description and explanation. To this end, we use an empirically relevant setting with…
Descriptors: Bayesian Statistics, Models, Decision Making, Comparative Analysis
Abdullah Mana Alfarwan – ProQuest LLC, 2024
This dissertation examined classification outcome differences among four popular individual supervised machine learning (ISML) models (logistic regression, decision tree, support vector machine, and multilayer perceptron) when predicting minor class membership within imbalanced datasets. The study context and the theoretical population sampled…
Descriptors: Regression (Statistics), Decision Making, Prediction, Sample Size
Hung, Su-Pin; Huang, Hung-Yu – Journal of Educational and Behavioral Statistics, 2022
To address response style or bias in rating scales, forced-choice items are often used to request that respondents rank their attitudes or preferences among a limited set of options. The rating scales used by raters to render judgments on ratees' performance also contribute to rater bias or errors; consequently, forced-choice items have recently…
Descriptors: Evaluation Methods, Rating Scales, Item Analysis, Preferences
Zhao, Xin; Coxe, Stefany; Sibley, Margaret H.; Zulauf-McCurdy, Courtney; Pettit, Jeremy W. – Prevention Science, 2023
There has been increasing interest in applying integrative data analysis (IDA) to analyze data across multiple studies to increase sample size and statistical power. Measures of a construct are frequently not consistent across studies. This article provides a tutorial on the complex decisions that occur when conducting harmonization of measures…
Descriptors: Data Analysis, Sample Size, Decision Making, Test Items
Toprak, Emre; Gelbal, Selahattin – International Journal of Assessment Tools in Education, 2020
This study aims to compare the performances of the artificial neural network, decision trees and discriminant analysis methods to classify student achievement. The study uses multilayer perceptron model to form the artificial neural network model, chi-square automatic interaction detection (CHAID) algorithm to apply the decision trees method and…
Descriptors: Comparative Analysis, Classification, Artificial Intelligence, Networks
Wulff, Dirk U.; Pachur, Thorsten – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2016
What are the cognitive mechanisms underlying subjective valuations formed on the basis of sequential experiences of an option's possible outcomes? Ashby and Rakow (2014) have proposed a sliding window model (SWIM), according to which people's valuations represent the average of a limited sample of recent experiences (the size of which is estimated…
Descriptors: Experimental Psychology, Cognitive Psychology, Modeling (Psychology), Models
Two Distinct Exploratory Behaviors in Decisions from Experience: Comment on Gonzalez and Dutt (2011)
Hills, Thomas T.; Hertwig, Ralph – Psychological Review, 2012
Gonzalez and Dutt (2011) recently reported that trends during sampling, prior to a consequential risky decision, reveal a gradual movement from exploration to exploitation. That is, even when search imposes no immediate costs, people adopt the same pattern manifest in costly search: early exploration followed by later exploitation. From this…
Descriptors: Decision Making, Models, Inferences, Sampling
Solomon, Benjamin G.; Forsberg, Ole J. – School Psychology Quarterly, 2017
Bayesian techniques have become increasingly present in the social sciences, fueled by advances in computer speed and the development of user-friendly software. In this paper, we forward the use of Bayesian Asymmetric Regression (BAR) to monitor intervention responsiveness when using Curriculum-Based Measurement (CBM) to assess oral reading…
Descriptors: Bayesian Statistics, Regression (Statistics), Least Squares Statistics, Evaluation Methods
Gonzalez, Cleotilde; Dutt, Varun – Psychological Review, 2012
Hills and Hertwig (2012) challenge the proposed similarity of the exploration-exploitation transitions found in Gonzalez and Dutt (2011) between the 2 experimental paradigms of decisions from experience (sampling and repeated-choice), which was predicted by an instance-based learning (IBL) model. The heart of their argument is that in the sampling…
Descriptors: Data, Models, Learning Processes, Criticism
Fiedler, Klaus; Kareev, Yaakov – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2006
Adaptive decision making requires that contingencies between decision options and their relative assets be assessed accurately and quickly. The present research addresses the challenging notion that contingencies may be more visible from small than from large samples of observations. An algorithmic account for such a seemingly paradoxical effect…
Descriptors: Sampling, Decision Making, Computer Simulation, Models

Halpin, Gerald; And Others – 1991
The objective of this investigation was to take a small data set that represents unbalanced factorial designs and explain by example how the variance is partitioned when using the various options from the Statistical Package for the Social Sciences (SPSSX) and Statistical Analysis System (SAS). That the unequal cell size analysis of variance…
Descriptors: Analysis of Variance, Computer Software Evaluation, Decision Making, Equations (Mathematics)