The controversy of significance testing: misconceptions and alternatives.
The current debate about the merits of null hypothesis significance testing, even though provocative, is not particularly novel. The significance testing approach has had defenders and opponents for decades, especially within the social sciences, where reliance on the use of significance testing has historically been heavy. The primary concerns have been (1) the misuse of significance testing, (2) the misinterpretation of P values, and (3) the lack of accompanying statistics, such as effect sizes and confidence intervals, that would provide a broader picture into the researcher's data analysis and interpretation. This article presents the current thinking, both in favor and against, on significance testing, the virtually unanimous support for reporting effect sizes alongside P values, and the overall implications for practice and application.
Glaser
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Pacific Science & Engineering Group, San Diego, Calif., USA.
D015982:Bias; D003627:Data Interpretation, Statistical; D015987:Effect Modifier, Epidemiologic; D006801:Humans; D015399:Nursing Research / Q000379:methods; D015203:Reproducibility of Results; D012107:Research Design / Q000592:standards / Q000639:trends