Type-1 error inflation in the traditional by-participant analysis to metamemory accuracy: a generalized mixed-effects model perspective

In order to examine metacognitive accuracy (i.e., the relationship between metacognitive judgment and memory performance), researchers often rely on by-participant analysis, where metacognitive accuracy (e.g., resolution, as measured by the gamma coefficient or signal detection measures) is computed for each participant and the computed values are entered into group-level statistical tests such as the t-test. In the current work, we argue that the by-participant analysis, regardless of the accuracy measurements used, would produce a substantial inflation of Type-1 error rates, when a random item effect is present. A mixed-effects model is proposed as a way to effectively address the issue, and our simulation studies examining Type-1 error rates indeed showed superior performance of mixed-effects model analysis as compared to the conventional by-participant analysis. We also present real data applications to illustrate further strengths of mixed-effects model analysis. Our findings imply that caution is needed when using the by-participant analysis, and recommend the mixed-effects model analysis.

Modified Fixed Effects Estimation of Technical Inefficiency

We consider method of moment fixed effects (FE) estimation of technical inefficiency. When N, the number of cross sectional observations, is large it ispossible to obtain consistent central moments of the population distribution of the inefficiencies. It is well-known that the traditional FE estimator may be seriously upward biased when N is large and T, the number of time observations, is small. Based on the second central moment and a single parameter distributional assumption on the inefficiencies, we obtain unbiased technical inefficiencies in large N settings. The proposed methodology bridges traditional FE and maximum likelihood estimation – bias is reduced without the random effects assumption.

A finite sample improvement of the fixed effects estimator : applied to technical infficiency

The FE ('fixed effects') estimator of technical inefficiency performs poorly when N ('number of firms') is large and T ('number of time observations') is small. We propose estimators of both the firm effects and the inefficiencies, which have small sample gains compared to the traditional FE estimator. The estimators are based on nonparametric kernel regression of unordered variables, which includes the FE estimator as a special case. In terms of global conditional MSE ('mean square error') criterions, it is proved that there are kernel estimators which are efficient to the FE estimators of firm effects and inefficiencies, in finite samples. Monte Carlo simulations supports our theoretical findings and in an empirical example it is shown how the traditional FE estimator and the proposed kernel FE estimator lead to very different conclusions about inefficiency of Indonesian rice farmers.

Examining Gender Differences in Received, Provided and Invisible Social Control: An Application of the Dual-Effects-Model

The dual-effects model of social control not only assumes that social control leads to better health practices but also arouses psychological distress. However, findings are inconsistent. The present study advances the current literature by examining social control from a dyadic perspective in the context of smoking. In addition, the study examines whether control, continuous smoking abstinence, and affect are differentially related for men and women. Before and three weeks after a self-set quit attempt, we examined 106 smokers (77 men, mean age: 40.67, average number of cigarettes smoked per day: 16.59 [SD=8.52, range=1-40] at baseline and 5.27 [SD=6.97, range=0-40] at follow-up) and their nonsmoking heterosexual partners, assessing received and provided control, continuous abstinence, and affect. With regard to smoker's affective reactions, partner's provided control was related to an increase in positive and to a decrease in negative affect, but only for female smokers. Moreover, the greater the discrepancy between smoker received and partner's provided control was the more positive affect increased and the more negative affect decreased, but again only for female smokers. These findings demonstrate that female smokers' well-being was raised over time if they were not aware of the control attempts of their nonsmoking partners, indicating positive effects of invisible social control. This study's results emphasize the importance of applying a dyadic perspective and taking gender differences in the dual-effects model of social control into account.

Social Support at the Workplace, Motivation to Transfer, and Training Transfer: A Multi-Level Indirect Effects Model

Supervisor support, peer support and transfer motivation have been identified as important predictors for training transfer. Transfer motivation is supposed to mediate the support–training transfer relationship. Especially after team training interventions that include all team members (i.e., intact-team training), individual perception of these factors might be shared among team members. However, an integration of the team level in the training transfer process is rare, yet still needed. Analyzing 194 employees from 34 teams in the context of intact-team training interventions, we found similar relationships and processes at both levels of analysis: Social support enhances transfer motivation at the individual and team levels. Furthermore, motivation to transfer increases training transfer and serves as a connecting mechanism in the social support–training transfer link. The results underline the importance of (1) considering multiple levels in theories and research about the training transfer process and (2) ensuring the practice of individual-directed support and a shared, supportive climate within teams.

Mixed effects model in negative exponential curve

Despite many researches on development in education and psychology, not often is the methodology tested with real data. A major barrier to test the growth model is that the design of study includes repeated observations and the nature of the growth is nonlinear. The repeat measurements on a nonlinear model require sophisticated statistical methods. In this study, we present mixed effects model in a negative exponential curve to describe the development of children's reading skills. This model can describe the nature of the growth on children's reading skills and account for intra-individual and inter-individual variation. We also apply simple techniques including cross-validation, regression, and graphical methods to determine the most appropriate curve for data, to find efficient initial values of parameters, and to select potential covariates. We illustrate with an example that motivated this research: a longitudinal study of academic skills from grade 1 to grade 12 in Connecticut public schools. ^

Supplementary tests of Masonboro Inlet fixed-bed model : hydraulic model investigation /

"General investigation of tidal inlets; a program of research conducted jointly by U.S. Army Coastal Engineering Research Center, Fort Belvoir, Virginia [and] U.S. Army Engineer Waterways Experiment Station, Vicksburg, Mississippi."

Statnote 9: The one-way analysis of variance (random effects model)

There is an alternative model of the 1-way ANOVA called the 'random effects' model or ‘nested’ design in which the objective is not to test specific effects but to estimate the degree of variation of a particular measurement and to compare different sources of variation that influence the measurement in space and/or time. The most important statistics from a random effects model are the components of variance which estimate the variance associated with each of the sources of variation influencing a measurement. The nested design is particularly useful in preliminary experiments designed to estimate different sources of variation and in the planning of appropriate sampling strategies.

Implementation of the EM Algorithm for Maximum Likelihood Estimation of a Random Effects Model for One Longitudinal Ordinal Outcome

2010 Mathematics Subject Classification: 62J99.

Aromatherapy for treatment of postoperative nausea and vomiting

Background: Postoperative nausea and vomiting is a common and unpleasant phenomenon and current therapies are not always effective for all patients. Aromatherapy has been suggested as a possible addition to the available treatment strategies. Objectives: This review sought to establish what effect the use of aromatherapy has on the severity and duration of established postoperative nausea and vomiting and whether aromatherapy can be used with safety and clinical effectiveness comparable to standard pharmacological treatments. Search methods: We searched the Cochrane Central Register of Controlled Trials (CENTRAL) (The Cochrane Library 2011, Issue 3); MEDLINE; EMBASE; CINAHL; CAM on PubMed; Meditext; LILACS database; and ISI Web of Science as well as grey literature sources and the reference lists of retrieved articles. We conducted database searches up to August 2011. Selection criteria: We included all randomized controlled trials (RCTs) and controlled clinical trials (CCTs) where aromatherapy was used to treat postoperative nausea and vomiting. Interventions were all types of aromatherapy. Aromatherapy was defined as the inhalation of the vapours of any substance for the purposes of a therapeutic benefit. Primary outcomes were the severity and duration of postoperative nausea and vomiting. Secondary outcomes were adverse reactions, use of rescue anti-emetics and patient satisfaction with treatment. Data collection and analysis: Two review authors assessed risk of bias in the included studies and extracted data. As all outcomes analysed were dichotomous, we used a fixed-effects model and calculated relative risk (RR) with associated 95% confidence interval (95% CI). Results: The nine included studies comprised six RCTs and three CCTs with a total of 402 participants. The mean age and range data for all participants were not reported for all studies. The method of randomization in four of the six included RCTs was explicitly stated and adequate. Incomplete reporting of data affected the completeness of the analysis. Compared with placebo, isopropyl alcohol vapour inhalation was effective in reducing the proportion of participants requiring rescue anti-emetics (RR 0.30, 95%CI 0.09 to 1.00, P = 0.05). However, compared with standard anti-emetic treatment, isopropyl alcohol was not effective in reducing the proportion of participants requiring rescue anti-emetics (RR 0.66 95%CI 0.39 to 1.13, P = 0.13) except when the data from a possibly confounded study were included (RR 0.66, 95% CI 0.45 to 0.98, P = 0.04). Where studies reported data on patient satisfaction with aromatherapy, there were no statistically significant differences between the groups (RR 1.12, 95%CI 0.62 to 2.03, P = 0.71). Authors' conclusions: Isopropyl alcohol was more effective than saline placebo for reducing postoperative nausea and vomiting but less effective than standard anti-emetic drugs. There is currently no reliable evidence for the use of peppermint oil.