{"title":"临床神经心理学研究中的抽样问题及非参数解。","authors":"M D Lezak, D K Gray","doi":"10.1080/01688638408401200","DOIUrl":null,"url":null,"abstract":"<p><p>Research data in clinical neuropsychology frequently do not conform to the requirements for parametric statistical analysis. In some of these cases, data analysis by parametric techniques does not identify existing differences. The usefulness of nonparametric statistical tools in evaluating irregular data sets is demonstrated in three cases examples. Methodological considerations arising from these examples are discussed.</p>","PeriodicalId":79225,"journal":{"name":"Journal of clinical neuropsychology","volume":"6 1","pages":"101-9"},"PeriodicalIF":0.0000,"publicationDate":"1984-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/01688638408401200","citationCount":"11","resultStr":"{\"title\":\"Sampling problems and nonparametric solutions in clinical neuropsychological research.\",\"authors\":\"M D Lezak, D K Gray\",\"doi\":\"10.1080/01688638408401200\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Research data in clinical neuropsychology frequently do not conform to the requirements for parametric statistical analysis. In some of these cases, data analysis by parametric techniques does not identify existing differences. The usefulness of nonparametric statistical tools in evaluating irregular data sets is demonstrated in three cases examples. Methodological considerations arising from these examples are discussed.</p>\",\"PeriodicalId\":79225,\"journal\":{\"name\":\"Journal of clinical neuropsychology\",\"volume\":\"6 1\",\"pages\":\"101-9\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1984-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1080/01688638408401200\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of clinical neuropsychology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/01688638408401200\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of clinical neuropsychology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/01688638408401200","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Sampling problems and nonparametric solutions in clinical neuropsychological research.
Research data in clinical neuropsychology frequently do not conform to the requirements for parametric statistical analysis. In some of these cases, data analysis by parametric techniques does not identify existing differences. The usefulness of nonparametric statistical tools in evaluating irregular data sets is demonstrated in three cases examples. Methodological considerations arising from these examples are discussed.
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