The classic edition of What If There Were No Significance Tests? highlights current statistical inference practices. Four areas are featured as essential for making inferences: sound judgment, meaningful research questions, relevant design, and assessing fit in multiple ways. Other options (data visualization, replication or meta-analysis), other features (mediation, moderation, multiple levels or classes), and other approaches (Bayesian analysis, simulation, data mining, qualitative inquiry) are also suggested.
The Classic Edition s new Introduction demonstrates the...
The classic edition of What If There Were No Significance Tests? highlights current statistical inference practices. Four areas are featured...
The classic edition of "What If There Were No Significance Tests?" highlights current statistical inference practices. Four areas are featured as essential for making inferences: sound judgment, meaningful research questions, relevant design, and assessing fit in multiple ways. Other options (data visualization, replication or meta-analysis), other features (mediation, moderation, multiple levels or classes), and other approaches (Bayesian analysis, simulation, data mining, qualitative inquiry) are also suggested.
The "Classic Edition s "new Introduction demonstrates the ongoing...
The classic edition of "What If There Were No Significance Tests?" highlights current statistical inference practices. Four areas are featured as e...
A debate stimulated by a recent meeting of the Society of Multivariate Experimental Psychology resulted in the publication of this book. Although the viewpoints span a range of perspectives, the overriding theme that emerges states that significance testing may still be useful if supplemented with some or all of the following - Bayesian logic, caution, confidence intervals, effect sizes and power, other goodness of approximation measures, replication and meta-analysis, sound reasoning, and theory appraisal and corroboration.
A debate stimulated by a recent meeting of the Society of Multivariate Experimental Psychology resulted in the publication of this book. Although the ...
Current interventions aimed at improving health and increasing engagement in exercise often cluster individuals into groups based on collective characteristics or norms in order to change a behavior. The challenge is to design interventions customized to a single individual based on his or her unique behavior, situation, and characteristics. More recent and rigorous statistical methods may be more appropriate for testing complex hypotheses pertaining to health and exercise behaviors. This book reviews multiple more rigorous and less widely used multivariate methods and measures for assessing...
Current interventions aimed at improving health and increasing engagement in exercise often cluster individuals into groups based on collective charac...
