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Mark Rubin
University of Newcastle, Australia
  1. Do P Values Lose Their Meaning in Exploratory Analyses? It Depends How You Define the Familywise Error Rate.Mark Rubin - 2017 - Review of General Psychology 21:269-275.
    Several researchers have recently argued that p values lose their meaning in exploratory analyses due to an unknown inflation of the alpha level (e.g., Nosek & Lakens, 2014; Wagenmakers, 2016). For this argument to be tenable, the familywise error rate must be defined in relation to the number of hypotheses that are tested in the same study or article. Under this conceptualization, the familywise error rate is usually unknowable in exploratory analyses because it is usually unclear how many hypotheses have (...)
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  2. What Type of Type I Error? Contrasting the Neyman–Pearson and Fisherian Approaches in the Context of Exact and Direct Replications.Mark Rubin - 2021 - Synthese 198 (6):5809–5834.
    The replication crisis has caused researchers to distinguish between exact replications, which duplicate all aspects of a study that could potentially affect the results, and direct replications, which duplicate only those aspects of the study that are thought to be theoretically essential to reproduce the original effect. The replication crisis has also prompted researchers to think more carefully about the possibility of making Type I errors when rejecting null hypotheses. In this context, the present article considers the utility of two (...)
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  3. When Does HARKing Hurt? Identifying When Different Types of Undisclosed Post Hoc Hypothesizing Harm Scientific Progress.Mark Rubin - 2017 - Review of General Psychology 21:308-320.
    Hypothesizing after the results are known, or HARKing, occurs when researchers check their research results and then add or remove hypotheses on the basis of those results without acknowledging this process in their research report (Kerr, 1998). In the present article, I discuss three forms of HARKing: (1) using current results to construct post hoc hypotheses that are then reported as if they were a priori hypotheses; (2) retrieving hypotheses from a post hoc literature search and reporting them as a (...)
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  4. The Costs of HARKing.Mark Rubin - forthcoming - British Journal for the Philosophy of Science:000-000.
    Kerr coined the term ‘HARKing’ to refer to the practice of ‘hypothesizing after the results are known’. This questionable research practice has received increased attention in recent years because it is thought to have contributed to low replication rates in science. The present article discusses the concept of HARKing from a philosophical standpoint and then undertakes a critical review of Kerr’s twelve potential costs of HARKing. It is argued that these potential costs are either misconceived, misattributed to HARKing, lacking evidence, (...)
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  5. An Evaluation of Four Solutions to the Forking Paths Problem: Adjusted Alpha, Preregistration, Sensitivity Analyses, and Abandoning the Neyman-Pearson Approach.Mark Rubin - 2017 - Review of General Psychology 21:321-329.
    Gelman and Loken (2013, 2014) proposed that when researchers base their statistical analyses on the idiosyncratic characteristics of a specific sample (e.g., a nonlinear transformation of a variable because it is skewed), they open up alternative analysis paths in potential replications of their study that are based on different samples (i.e., no transformation of the variable because it is not skewed). These alternative analysis paths count as additional (multiple) tests and, consequently, they increase the probability of making a Type I (...)
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  6.  53
    “Repeated Sampling From the Same Population?” A Critique of Neyman and Pearson’s Responses to Fisher.Mark Rubin - 2020 - European Journal for Philosophy of Science 10 (3):1-15.
    Fisher criticised the Neyman-Pearson approach to hypothesis testing by arguing that it relies on the assumption of “repeated sampling from the same population.” The present article considers the responses to this criticism provided by Pearson and Neyman. Pearson interpreted alpha levels in relation to imaginary replications of the original test. This interpretation is appropriate when test users are sure that their replications will be equivalent to one another. However, by definition, scientific researchers do not possess sufficient knowledge about the relevant (...)
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