Canadian Journal of Experimental Psychology

Canadian Journal of Experimental Psychology is a magazine focusing on Canadian Experimental Psychology

Articles from Vol. 57, No. 3, September

A Further Look at the "Language-as-Fixed-Effect Fallacy"
Abstract The proper analysis of experiments using language materials has been a source of controversy and debate among researchers. We summarize the main issues and discuss the solutions that have been presented. Even though the major issues have been...
Basic Statistics and the Inconsistency of Multiple Comparison Procedures
Abstract This paper has two main themes. First, the various statistical measures used in this journal are summarized and their interrelationships described by way of a flow chart. These are the pooled standard deviation, the pooled variance or mean square...
Effect Sizes for Experimenting Psychologists
Until quite recently in the history of experimental psychology, when researchers spoke of "the results of a study," they almost invariably were referring to whether they had been able to "reject the null hypothesis," that is, to whether the p values...
Introduction to the Special Issue on Alternative Methods of Data Interpretation
Shortly after assuming his editorship of the Canadian Journal of Experimental Psychology, Peter Dixon discussed with me the possibility of guest editing a special issue of the Journal, possibly on the general topic of alternative methods of data analysis....
Is the Area Measure a Historical Anomaly?
Abstract Green's well-known area theorem establishes an equivalence between the area under the yes-no ROC curve and the percent correct of an unbiased observer in a two-alternative forced-choice (2AFC) task with equivalent stimuli. In this article, we...
Multiway Frequency Analysis for Experimental Psychologists
Abstract Many research designs in experimental psychology generate data that are fundamentally discrete or categorical in nature, and produce multiway tables of frequencies. Despite an extensive and, more recently, accessible literature on the topic,...
Statistical Testing and Null Distributions: What to Do When Samples Are Not Random
Abstract Selected literature related to statistical testing is reviewed to compare the theoretical models underlying parametric and nonparametric inference. Specifically, we show that these models evaluate different hypotheses, are based on different...
The P-Value Fallacy and How to Avoid It
Abstract Null hypothesis significance tests are commonly used to provide a link between empirical evidence and theoretical interpretation. However, this strategy is prone to the "p-value fallacy" in which effects and interactions are classified as either...
Using Confidence Intervals for Graphically Based Data Interpretation*
Abstract As a potential alternative to standard null hypothesis significance testing, we describe methods for graphical presentation of data - particularly condition means and their corresponding confidence intervals - for a wide range of factorial designs...
Using the Analysis of Covariance to Increase the Power of Priming Experiments
Abstract Although priming paradigms are widely used in cognitive psychology, the statistical analyses typically applied to priming data may not be optimal. Conceiving of priming paradigms as change-from-baseline designs suggests that the analysis of...
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