Increasing Your Statistical Edge: Dealing With Nested Data Structures For many speech-language researchers, it’s perhaps been some time since completing formal course work in statistics. I would also suspect, based on my own experience, that the statistics courses many of us did take may not have been as rigorous or comprehensive as those that researchers-in-training are required to ... Editorial
Editorial  |   August 01, 2009
Increasing Your Statistical Edge: Dealing With Nested Data Structures
 
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Editorial
Editorial   |   August 01, 2009
Increasing Your Statistical Edge: Dealing With Nested Data Structures
American Journal of Speech-Language Pathology, August 2009, Vol. 18, 210-211. doi:10.1044/1058-0360(2009/ed-03)
 
American Journal of Speech-Language Pathology, August 2009, Vol. 18, 210-211. doi:10.1044/1058-0360(2009/ed-03)
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For many speech-language researchers, it’s perhaps been some time since completing formal course work in statistics. I would also suspect, based on my own experience, that the statistics courses many of us did take may not have been as rigorous or comprehensive as those that researchers-in-training are required to take, or at least have the opportunity to take, these days. It is not uncommon for my current doctoral advisees to take a multiyear sequence of statistics courses that includes not only the traditional courses (e.g., analysis of variance [ANOVA], multivariate analysis of variance [MANOVA], and regression analysis) but also such courses as structural equation modeling, categorical variables, growth curve analyses, item response theory, and hierarchical linear modeling (HLM). The implication of this is that shortly into their doctoral training, my students know a lot more than I do about a variety of advanced statistical techniques.
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