Kirjahaku

This succinct and jargon-free introduction to effect sizes gives students and researchers the tools they need to interpret the practical significance of their results. Using a class-tested approach that includes numerous examples and step-by-step exercises, it introduces and explains three of the most important issues relating to the practical significance of research results: the reporting and interpretation of effect sizes (Part I), the analysis of statistical power (Part II), and the meta-analytic pooling of effect size estimates drawn from different studies (Part III). The book concludes with a handy list of recommendations for those actively engaged in or currently preparing research projects.

Want to do research that matters? Want results that make sense?This jargon-free introduction to effect sizes will show you how to the answer the dreaded "So what?" question. It will teach you how to interpret the substantive as opposed to the statistical significance of your results.Find out why your estimate of the effect size is the primary output of your studyLearn how to calculate effect sizes in a variety of metricsBoost your publication prospects by interpreting the real-world significance of your resultsDiscover the difference between an effect size and a p-valueUnderstand the critical role of effect sizes in power- and meta-analysesAnd that's just for starters Give journal editors what they are asking for - results that are engaging and relevant to stakeholders. Using a class-tested approach, Effect Size Matters will provide you with the tools to meaningfully interpret the results of your research. Book 1 of 3 in the MadMethods series. (Get all three books for less than the price of two with MadMethods 1-3 )Get your copy now

Does your study have the power to find what you are looking for? Or are you betting your career on a project that is designed to fail?Many studies lack the statistical power to find effects. This jargon-free guide will show you how to design studies that succeed Learn how, why, and when to analyze statistical powerBoost your funding prospects with power analyses that dazzleFind out how to calculate sample sizesLearn strategies for boosting the power of under-powered studiesDiscover why too much power can be as bad as too littleMaster five techniques for minimizing the threat of Type II errorsUnderstand the dangers of fishing in the dataBe amazed by the stunning conclusions of power researchAnd that's just for starters Why waste resources on projects that are set up to fail? Statistical Power Trip will show you how to design studies that win grants and get published Book 2 of 3 in the MadMethods series. (Get all three books for less than the price of two with MadMethods 1-3 )Get your copy now

Will your research make a unique contribution? Or are you reinventing the wheel?This jargon-free guide to meta-analysis will show you how to draw conclusions even from inconclusive studies and discover untapped gold mines for further research.Learn how to pool effect sizes from past researchDiscover patterns of meaning in disparate resultsHarvest effect sizes that are essential for power analysesEstablish nonzero benchmarks more meaningful than the nullUncover the influence of meta-moderators that no one else has seenFind remedies for overcoming the availability biasAnd much more Using a class-tested approach, Meta-Analysis Made Easy will give you the tools to make sense of past research and identify the most fruitful avenues for future inquiry Book 3 in the MadMethods series. (Get all three books for less than the price of two with MadMethods 1-3 )Get your copy now