Conventional random-effects models in meta-analysis rely on large sample approximations instead of exact small sample results. While random-effects methods produce efficient estimates and confidence intervals for the summary effect have correct coverage when the number of studies is sufficiently large, we demonstrate that conventional methods…

Spatial microsimulation encompasses a range of alternative methodological approaches for the small area estimation (SAE) of target population parameters from sample survey data down to target small areas in contexts where such data are desired but not otherwise available. Although widely used, an enduring limitation of spatial microsimulation SAE…

Bayesian inference for structural equation models (SEMs) is increasingly popular in social and psychological sciences owing to its flexibility to adapt to more complex models and the ability to include prior information if available. However, there are two major hurdles in using the traditional Bayesian SEM in practice: (1) the information nested…

Contribution: Two general rules for calculating, in the time domain, step discontinuities of voltages and currents in electric circuits, combining physical principles and basic mathematical treatment. The two general rules, resulting from a formal method of analysis, provide a straightforward way to update the states of a circuit, immediately…

Molecular-, fluid- and field-dynamics simulation are becoming more mainstream tools for practicing process engineers; here, the academic community needs to pay close attention to "upskilling" demands from industry, where remote working/training emphasizes the need for sophisticated computational-engineering design tools with molecular…

Equilibrium is an essential concept in undergraduate physics curriculum as it integrates Newton's laws and torque. The importance also comes from its wide applications in mechanics and biomechanics. Simulations of Back and Arms are developed mainly for the undergraduates who major in physical therapy and health sciences. They are implemented as…

This article describes (1) the survey methodological and statistical characteristics of the nonrandomized method for surveying sensitive questions for both cross-sectional and panel survey data and (2) the way to use the incompletely observed variable obtained from this survey method in logistic regression and in loglinear and log-multiplicative…

This paper revisits the use of effect sizes in the analysis of experimental and similar results, and reminds readers of the relative advantages of the mean absolute deviation as a measure of variation, as opposed to the more complex standard deviation. The mean absolute deviation is easier to use and understand, and more tolerant of extreme…

De la Torre and Deng suggested a resampling-based approach for person-fit assessment (PFA). The approach involves the use of the [math equation unavailable] statistic, a corrected expected a posteriori estimate of the examinee ability, and the Monte Carlo (MC) resampling method. The Type I error rate of the approach was closer to the nominal level…

The objective of this work is to present a spreadsheet tool that illustrates an ideal case of dynamic matrix control (DMC) calculations. The ideal case presented in this work is a hypothetical single- input-single-output DMC control system for setpoint tracking, in the absence of disturbance and mismatch between the measured and predicted process…

The focus of the current proposal is to examine the effect of two dynamic simulations on the participants' conceptions of rate of change. Conceptions of rate of change were measured according to Carlson et al.'s (2002) Mental Actions framework and how the participants related the physical simulations to the graphical representations (Heid, et al.,…

Biased sampling occurs frequently in economics, epidemiology, and medical studies either by design or due to data collecting mechanism. Failing to take into account the sampling bias usually leads to incorrect inference. We propose a unified estimation procedure and a computationally fast resampling method to make statistical inference for…

When cut scores for classifications occur on the total score scale, popular methods for estimating classification accuracy (CA) and classification consistency (CC) require assumptions about a parametric form of the test scores or about a parametric response model, such as item response theory (IRT). This article develops an approach to estimate CA…

Generalized linear mixed models are frequently applied to data with clustered categorical outcomes. The effect of clustering on the response is often difficult to practically assess partly because it is reported on a scale on which comparisons with regression parameters are difficult to make. This article proposes confidence intervals for…

In a provocative and influential paper, Jesse Rothstein (2010) finds that standard value-added models (VAMs) suggest implausible future teacher effects on past student achievement, a finding that obviously cannot be viewed as causal. This is the basis of a falsification test (the Rothstein falsification test) that appears to indicate bias in VAM…