Applied researchers often find themselves making statistical inferences in settings that would seem to require multiple comparisons adjustments. We challenge the Type I error paradigm that underlies these corrections. Moreover we posit that the problem of multiple comparisons can disappear entirely when viewed from a hierarchical Bayesian…

When conducting item reviews, analysts evaluate an array of statistical and graphical information to assess the fit of a field test (FT) item to an item response theory model. The process can be tedious, particularly when the number of human reviews (HR) to be completed is large. Furthermore, such a process leads to decisions that are susceptible…

The methods and models for categorical data analysis cover considerable ground, ranging from regression-type models for binary and binomial data, count data, to ordered and unordered polytomous variables, as well as regression models that mix qualitative and continuous data. This article focuses on methods for binary or binomial data, which are…

The study of prediction bias is important and the last five decades include research studies that examined whether test scores differentially predict academic or employment performance. Previous studies used ordinary least squares (OLS) to assess whether groups differ in intercepts and slopes. This study shows that OLS yields inaccurate inferences…

By using a sample of 1st-year undergraduate business students, this study dealt with the development of simple (deterministic and non-optimization) spreadsheet models of income statements within an introductory course on business informatics. The study examined students' errors in doing this for business situations of their choice and found three…

The authors examined the robustness of multilevel linear growth curve modeling to misspecification of an autoregressive moving average process. As previous research has shown (J. Ferron, R. Dailey, & Q. Yi, 2002; O. Kwok, S. G. West, & S. B. Green, 2007; S. Sivo, X. Fan, & L. Witta, 2005), estimates of the fixed effects were unbiased, and Type I…

An analytical technique is reviewed that allows a researcher to decompose informant reports into their respective trait, informant bias, and measure specificity using LISREL. The technique is illustrated in a study of decision making in 151 police agencies. (SLD)

Answers to theoretical questions about the place of input in a formal second language acquisition model are dependent on a distinction between two kinds of learner hypotheses. Type-N hypotheses require "negative evidence" for testing, while Type-P hypotheses are tested on the basis of "positive data" alone. (Author/CB)

A theory of sentence production is presented that accounts for facts about speech errors, including (1) the kinds of errors that occur; (2) the constraints on their form; and (3) the conditions that precipitate them. Two simulation models are introduced to illustrate how the theory applies to phonological encoding processes. (Author/LMO)

Presents five simulation models reflecting sequential levels of children's simple arithmetic story problem solving skills. Outputs of the models are compared with data obtained by presenting 60 five- to eight-year-olds with change problems to examine models' deterministic nature. Results indicate the models give an adequate description of behavior…

Parameters and procedures for developing an error-prone model (EPM) to predict financial aid applicants who are likely to misreport on Basic Educational Opportunity Grant (BEOG) applications are introduced. Specifications to adapt these general parameters to secondary data analysis of the Validation, Edits, and Applications Processing Systems…

The impact of quality assurance procedures on the correct award of Basic Educational Opportunity Grants (BEOGs) for 1979-1980 was assessed, and a model for detecting error-prone applications early in processing was developed. The Bureau of Student Financial Aid introduced new comments into the edit system in 1979 and expanded the pre-established…

An evaluation of existing and proposed mechanisms to ensure data accuracy for the Pell Grant program is reported, and recommendations for efficient detection of fraud and error in the program are offered. One study objective was to examine the existing system of pre-established criteria (PEC), which are validation criteria that select students on…

An error-prone model (EPM) to predict financial aid applicants who are likely to misreport on Basic Educational Opportunity Grant (BEOG) applications was developed, based on interviews conducted with a quality control sample of 1,791 students during 1978-1979. The model was designed to identify corrective methods appropriate for different types of…

The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…