G*Power (Erdfelder, Faul, & Buchner, 1996) was designed as a general stand-alone power analysis program for statistical tests commonly used in social and behavioral research. G*Power 3 is a major extension of, and improvement over, the previous versions. It runs on widely used computer platforms (i.e., Windows XP, Windows Vista, and Mac OS X 10.4) and covers many different statistical tests of thet, F, and χ2 test families. In addition, it includes power analyses forz tests and some exact tests. G*Power 3 provides improved effect size calculators and graphic options, supports both distribution-based and design-based input modes, and offers all types of power analyses in which users might be interested. Like its predecessors, G*Power 3 is free.

https://link.springer.com/content/pdf/10.3758/BF03193146.pdf

G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences

G*Power is a free power analysis program for a variety of statistical tests. We present extensions and improvements of the version introduced by Faul, Erdfelder, Lang, and Buchner (2007) in the domain of correlation and regression analyses. In the new version, we have added procedures to analyze the power of tests based on (1) single-sample tetrachoric correlations, (2) comparisons of dependent correlations, (3) bivariate linear regression, (4) multiple linear regression based on the random predictor model, (5) logistic regression, and (6) Poisson regression. We describe these new features and provide a brief introduction to their scope and handling.

/pdf/statistical-power-analyses-using-g-power-3-1-tests-for-dnxl4mlxpv.pdf

Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses.

A study with low statistical power has a reduced chance of detecting a true effect, but it is less well appreciated that low power also reduces the likelihood that a statistically significant result reflects a true effect. Here, we show that the average statistical power of studies in the neurosciences is very low. The consequences of this include overestimates of effect size and low reproducibility of results. There are also ethical dimensions to this problem, as unreliable research is inefficient and wasteful. Improving reproducibility in neuroscience is a key priority and requires attention to well-established but often ignored methodological principles.

/pdf/power-failure-why-small-sample-size-undermines-the-4ftwwuexp7.pdf

Power failure: why small sample size undermines the reliability of neuroscience

Effect sizes are the most important outcome of empirical studies. Most articles on effect sizes highlight their importance to communicate the practical significance of results. For scientists themselves, effect sizes are most useful because they facilitate cumulative science. Effect sizes can be used to determine the sample size for follow-up studies, or examining effects across studies. This article aims to provide a practical primer on how to calculate and report effect sizes for t-tests and ANOVA’s such that effect sizes can be used in a-priori power analyses and meta-analyses. Whereas many articles about effect sizes focus on between-subjects designs and address within-subjects designs only briefly, I provide a detailed overview of the similarities and differences between within- and between-subjects designs. I suggest that some research questions in experimental psychology examine inherently intra-individual effects, which makes effect sizes that incorporate the correlation between measures the best summary of the results. Finally, a supplementary spreadsheet is provided to make it as easy as possible for researchers to incorporate effect size calculations into their workflow.

/pdf/calculating-and-reporting-effect-sizes-to-facilitate-4a429kama3.pdf

Calculating and reporting effect sizes to facilitate cumulative science: a practical primer for t-tests and ANOVAs

This work was supported by grants from the National Institutes of Health (R01 AG048814, B.A.B.; RO1 DA15043, B.A.B.; P50 NS38377, V.L.D. and T.M.D.) Christopher and Dana Reeve Foundation (B.A.B.), the Novartis Institute for Biomedical Research (B.A.B.), Dr. Miriam and Sheldon G. Adelson Medical Research Foundation (B.A.B.), the JPB Foundation (B.A.B., T.M.D.), the Cure Alzheimer’s Fund (B.A.B.), the Glenn Foundation (B.A.B.), the Esther B O’Keeffe Charitable Foundation (B.A.B.), the Maryland Stem Cell Research Fund (2013-MSCRFII-0105-00, V.L.D.; 2012-MSCRFII-0268-00, T.M.D.; 2013-MSCRFII-0105-00, T.M.D.; 2014-MSCRFF-0665, M.K.). S.A.L. was supported by a postdoctoral fellowship from the Australian National Health and Medical Research Council (GNT1052961), and the Glenn Foundation Glenn Award. L.E.C. was funded by a Merck Research Laboratories postdoctoral fellowship (administered by the Life Science Research Foundation). W.-S.C. was supported by a career transition grant from NEI (K99EY024690). C.J.B. was supported by a postdoctoral fellowship from Damon Runyon Cancer Research Foundation (DRG-2125-12). L.S. was supported by a postdoctoral fellowship from the German Research Foundation (DFG, SCHI 1330/1-1).

/pdf/neurotoxic-reactive-astrocytes-are-induced-by-activated-33z6oieelb.pdf

Neurotoxic reactive astrocytes are induced by activated microglia

S. Nishida and M. Shinya (1998) found that observers have only a limited ability to recover surface-reflectance properties under changes in surface shape. Our aim in the present study was to investigate how the degree of surface-reflectance constancy depends on the availability of information that may help to infer the reflectance and shape properties of surfaces. To this end, we manipulated the availability of (i) motion-induced information (static vs. dynamic presentation), (ii) disparity information (with the levels "monocular," "surface disparity," and "surface + highlight disparity"), and (iii) color information (grayscale stimuli vs. hue differences between diffuse and specular reflections). The task of the subjects was to match the perceived lightness and glossiness between two surfaces with different spatial frequency and amplitude by manipulating the diffuse component and the exponent of the Phong lighting model in one of the surfaces. Our results indicate that all three types of information improve the constancy of glossiness matches--both in isolation and in combination. The lightness matching data only revealed an influence of motion and color information. Our results indicate, somewhat counterintuitively, that motion information has a detrimental effect on lightness constancy.

Disparity, motion, and color information improve gloss constancy performance.

Although current theories of color vision differ in many respects, they all assume the existence of a uniquely defined neutral point in chromaticity space. It generally is assumed that this point satisfies several criteria simultaneously. One of these criteria is that it is perceived as achromatic. A further criterion shared by most theories is the structural assumption that lines in chromaticity space of constant hue converge on the neutral point. The basic assumption that these two criteria coincide is clearly true for isolated spots of light presented in darkness, and it usually is taken for granted that this coincidence generalizes to more complex visual stimuli. Here, we show that this is not the case. Our experiments with infields in chromatic surrounds revealed that the point in chromaticity space that appears gray is clearly different from the point on which lines of constant hue converge. A plausible interpretation of this apparently paradoxical finding in terms of color scission is proposed.

https://www.pnas.org/content/pnas/99/20/13352.full.pdf

The natural center of chromaticity space is not always achromatic: A new look at color induction

Variants of Metelli’s episcotister model, which are based on additive color mixture, have been found to describe the luminance conditions for perceptual transparency very accurately. However, the findings in the chromatic domain are not that clear-cut, since there exist chromatic stimuli that conform to the additive model but do not appear transparent. We present evidence that such failures are of a systematic nature, and we propose an alternative psychophysical model based on subtractive color mixture. Results of a computer simulation revealed that this model approximately describes color changes that occur when a surface is covered by a filter. We present the results of two psychophysical experiments with chromatic stimuli, in which we directly compared the predictions of the additive model and the predictions of the new model. These results show that the color relations leading to the perception of a homogeneous transparent layer conform very closely to the predictions of the new model and deviate systematically from the predictions of the additive model.

/pdf/psychophysical-model-of-chromatic-perceptual-transparency-3pakvkwou4.pdf

Psychophysical model of chromatic perceptual transparency based on substractive color mixture

http://www.uni-kiel.de/psychologie/psychophysik/preprintSimultan.pdf

The peculiar nature of simultaneous colour contrast in uniform surrounds

The disparity of highlights on specular reflecting surfaces usually differs from the disparity of the surface points. A. Kirschmann (1895) proposed that this fact may be used as a binocular cue for gloss perception. This was confirmed by A. Blake and H. Bulthoff (1990) who found that subjects judged the glossiness of convex ellipsoidal surfaces as most realistic if the disparity of the highlights was close to the physical correct one. Extending on this finding, we investigate more closely whether the effect of highlight disparity depends on the sharpness of the highlight and the relative amount of diffuse and specular reflection. We measured the effect of highlight disparity on both perceived strength and perceived authenticity of gloss. We used complex, three-dimensional curved surfaces that were stereoscopically presented on a CRT. The reflection characteristics were varied using the Phong lighting model. Highlights were presented either with or without highlight disparity. In a rating experiment, subjects were asked to judge the strength and the authenticity of the perceived surface glossiness. The presence of highlight disparity lead to an enhancement of both the authenticity and the strength of perceived glossiness. The latter finding was confirmed in an additional matching experiment.

Franz Faul

Papers

Disparity, motion, and color information improve gloss constancy performance.

The natural center of chromaticity space is not always achromatic: A new look at color induction

Psychophysical model of chromatic perceptual transparency based on substractive color mixture

The peculiar nature of simultaneous colour contrast in uniform surrounds

Highlight disparity contributes to the authenticity and strength of perceived glossiness.