Traditional and Rank-Based Tests for Ordered Alternatives in a Cluster Correlated Model

Psychometrika - Methods for the analysis of one-factor randomized groups designs with ordered treatments are well established, but they do not apply in the case of more complex experiments. This...     

A robust method for the analysis of experiments with ordered treatment levels.

A robust approach for the analysis of experiments with ordered treatment levels is presented as an alternative to existing approaches such as the parametric Abelson-Tukey test for monotone alternatives and the nonparametric Terpstra-Jonckheere test. The method integrates the familiar Spearman rank-order correlation with bootstrap routines to provide magnitude of association measures, p values, and confidence intervals for magnitude of association measures. The advantages of this method relative to five alternative approaches are pointed out.     

A double bootstrap method to analyze linear models with autoregressive error terms

A new method for the analysis of linear models that have autoregressive errors is proposed. The approach is not only relevant in the behavioral sciences for analyzing small-sample time-series intervention models, but it is also appropriate for a wide class of small-sample linear model problems in which there is interest in inferential statements regarding all regression parameters and autoregressive parameters in the model. The methodology includes a double application of bootstrap procedures. The 1st application is used to obtain bias-adjusted estimates of the autoregressive parameters. The 2nd application is used to estimate the standard errors of the parameter estimates. Theoretical and Monte Carlo results are presented to demonstrate asymptotic and small-sample properties of the method; examples that illustrate advantages of the new approach over established time-series methods are described.     

The effects of behavioral history on response acquisition with immediate and delayed reinforcement

Effects of prior exposure to the experimental chamber with levers present or absent and variable-time (VT) 60-s water deliveries arranged during one, five, or no 1-hr sessions were examined in rats during a 6-hr response-acquisition session in which presses on one lever produced water delivery immediately or after a 15-s resetting delay, and presses on the other lever canceled scheduled water deliveries. Response acquisition was (a) slower to occur when water deliveries were delayed, (b) most consistent in groups that had received five VT sessions, and (c) impaired by the presence of levers only when there had been five VT sessions and water deliveries were delayed during the acquisition session.     

The neural underpinnings of facial emotion recognition in ischemic stroke patients

Deficits in facial emotion recognition occur frequently after stroke, with adverse social and behavioural consequences. The aim of this study was to investigate the neural underpinnings of the recognition of emotional expressions, in particular of the distinct basic emotions (anger, disgust, fear, happiness, sadness and surprise). A group of 110 ischaemic stroke patients with lesions in (sub)cortical areas of the cerebrum was included. Emotion recognition was assessed with the Ekman 60 Faces Test of the FEEST. Patient data were compared to data of 162 matched healthy controls (HC’s). For the patients, whole brain voxel-based lesion–symptom mapping (VLSM) on 3-Tesla MRI images was performed. Results showed that patients performed significantly worse than HC’s on both overall recognition of emotions, and specifically of disgust, fear, sadness and surprise. VLSM showed significant lesion–symptom associations for FEEST total in the right fronto-temporal region. Additionally, VLSM for the distinct emotions showed, apart from overlapping brain regions (insula, putamen and Rolandic operculum), also regions related to specific emotions. These were: middle and superior temporal gyrus (anger); caudate nucleus (disgust); superior corona radiate white matter tract, superior longitudinal fasciculus and middle frontal gyrus (happiness) and inferior frontal gyrus (sadness). Our findings help in understanding how lesions in specific brain regions can selectively affect the recognition of the basic emotions.     

Prospective associations between marital adjustment and life satisfaction

Actor and partner effects for the 2‐year longitudinal associations between marital adjustment and life satisfaction were evaluated in a population‐based sample of middle‐aged and older adults (N = 1,385 couples). Results showed that (a) higher marital adjustment at baseline predicted higher life satisfaction at follow‐up, (b) higher life satisfaction at baseline predicted higher marital adjustment at follow‐up, (c) marital adjustment more strongly predicted life satisfaction than life satisfaction predicted marital adjustment for women, and (d) higher partner marital adjustment at baseline predicted higher life satisfaction at follow‐up. Results suggest that marital adjustment and life satisfaction influence one another in a bidirectional fashion and that the direction is predominantly from marital adjustment to life satisfaction in women.     

Measuring emotion recognition: Added value in diagnosing dementia of the Alzheimer’s disease type

Neuropsychological tests, particularly for episodic memory, are used to classify patients in memory clinics. Still, the differential diagnosis between dementia of the Alzheimer’s disease type (Dementia-AD), mild cognitive impairment (MCI), or major depressive disorder (MDD) is challenging. However, impairments in other domains, such as emotion recognition, an aspect of social cognition, might have additional value in distinguishing Dementia-AD from MCI and MDD and hence signal progression of neurodegeneration. We evaluated this in patients visiting a memory clinic. Sixty healthy controls (HC) and 143 first time attendants of an academic hospital memory clinic who were eventually classified as Dementia-AD (n = 45), MCI (n = 47), MDD (n = 27), or No Impairment (NI, n = 24) were included. We assessed group differences in Emotion Recognition (Ekman 60 Faces Test (EFT)) and episodic memory (Dutch Rey Auditory Verbal Learning Test (RAVLT)). With multinomial and binomial regression analysis, we assessed whether EFT was added to RAVLT in distinguishing patient groups. Dementia-AD patients had significantly worse emotion recognition than HC, MCI, MDD, and NI groups, but no other between-group differences were found. Episodic memory was impaired in Dementia-AD and MCI patients. We found no memory impairments in the MDD and NI groups. Emotion recognition in addition to episodic memory was significantly better in predicting group membership than episodic memory alone. In conclusion, emotion recognition measurement had added value for differentiation between patients first visiting memory clinics, in particular in distinguishing Dementia-AD from MCI. We recommend the standard inclusion of emotion recognition testing in neuropsychological assessment in memory clinics.     

An improved portmanteau test for autocorrelated errors in interrupted time-series regression models

A new portmanteau test for autocorrelation among the errors of interrupted time-series regression models is proposed. Simulation results demonstrate that the inferential properties of the proposed Q(H-M) test statistic are considerably more satisfactory than those of the well known Ljung-Box test and moderately better than those of the Box-Pierce test. These conclusions generally hold for a wide variety of autoregressive (AR), moving averages (MA), and ARMA error processes that are associated with time-series regression models of the form described in Huitema and McKean (2000a, 2000b).     

A simple and powerful test for autocorrelated errors in OLS intervention models

The important assumption of independent errors should be evaluated routinely in the application of interrupted time-series regression models. The two most frequently recommended tests of this assumption [Mood's runs test and the Durbin-Watson (D-W) bounds test] have several weaknesses. The former has poor small sample Type I error performance and the latter has the bothersome property that results are often declared to be "inconclusive." The test proposed in this article is simple to compute (special software is not required), there is no inconclusive region, an exact p-value is provided, and it has good Type I error and power properties relative to competing procedures. It is shown that these desirable properties hold when design matrices of a specified form are used to model the response variable. A Monte Carlo evaluation of the method, including comparisons with other tests (viz., runs, D-W bounds, and D-W beta), and examples of application are provided.