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Criticism 4 of NHST: No Mechanism for Producing Substantive Cumulative Knowledge

[Note to the Reader: This is a much rougher piece than the previous pieces because the argument is more complex. I ask that you please point out places where things are unclear and where claims are not rigorous.] In this fourth part of my series of criticisms of NHST, I’m going to focus on broad […]

Criticism 3 of NHST: Essential Information is Lost When Transforming 2D Data into a 1D Measure

Criticism 3 of NHST: Essential Information is Lost When Transforming 2D Data into a 1D Measure

Introduction Continuing on with my series on the weaknesses of NHST, I’d like to focus on an issue that’s not specific to NHST, but rather one that’s relevant to all quantitative analysis: the destruction caused by an inappropriate reduction of dimensionality. In our case, we’ll be concerned with the loss of essential information caused by […]

Criticism 2 of NHST: NHST Conflates Rare Events with Evidence Against the Null Hypothesis

Introduction This is my second post in a series describing the weaknesses of the NHST paradigm. In the first post, I argued that NHST is a dangerous tool for a community of researchers because p-values cannot be interpreted properly without perfect knowledge of the research practices of other scientists — knowledge that we cannot hope […]

Criticism 1 of NHST: Good Tools for Individual Researchers are not Good Tools for Research Communities

Introduction Over my years as a graduate student, I have built up a long list of complaints about the use of Null Hypothesis Significance Testing (NHST) in the empirical sciences. In the next few weeks, I’m planning to publish a series of blog posts, each of which will articulate one specific weakness of NHST. The […]

cumplyr: Extending the plyr Package to Handle Cross-Dependencies

Introduction For me, Hadley Wickham‘s reshape and plyr packages are invaluable because they encapsulate omnipresent design patterns in statistical computing: reshape handles switching between the different possible representations of the same underlying data, while plyr automates what Hadley calls the Split-Apply-Combine strategy, in which you split up your data into several subsets, perform some computation […]