Posts Tagged ‘ Miscellaneous Statistics ’

Looking for rigor in all the wrong places

January 21, 2017
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Looking for rigor in all the wrong places

My talk in the upcoming conference on Inference from Non Probability Samples, 16-17 Mar in Paris: Looking for rigor in all the wrong places What do the following ideas and practices have in common: unbiased estimation, statistical significance, insistence on random sampling, and avoidance of prior information? All have been embraced as ways of enforcing […] The post Looking for rigor in all the wrong places appeared first on Statistical…

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“Estimating trends in mortality for the bottom quartile, we found little evidence that survival probabilities declined dramatically.”

January 19, 2017
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“Estimating trends in mortality for the bottom quartile, we found little evidence that survival probabilities declined dramatically.”

Last year there was much discussion here and elsewhere about a paper by Anne Case and Angus Deaton, who noticed that death rates for non-Hispanic white Americans aged 45-54 had been roughly flat since 1999, even while the death rates for this age category had been declining steadily in other countries and among nonwhite Americans. […] The post “Estimating trends in mortality for the bottom quartile, we found little evidence…

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To know the past, one must first know the future: The relevance of decision-based thinking to statistical analysis

January 15, 2017
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We can break up any statistical problem into three steps: 1. Design and data collection. 2. Data analysis. 3. Decision making. It’s well known that step 1 typically requires some thought of steps 2 and 3: It is only when you have a sense of what you will do with your data, that you can […] The post To know the past, one must first know the future: The relevance…

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Frank Harrell statistics blog!

January 14, 2017
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Frank Harrell, author of an influential book on regression modeling and currently both a biostatistics professor and a statistician at the Food and Drug Administration, has started a blog. He sums up “some of his personal philosophy of statistics” here: Statistics needs to be fully integrated into research; experimental design is all important Don’t be […] The post Frank Harrell statistics blog! appeared first on Statistical Modeling, Causal Inference, and…

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Problems with “incremental validity” or more generally in interpreting more than one regression coefficient at a time

January 13, 2017
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Problems with “incremental validity” or more generally in interpreting more than one regression coefficient at a time

Kevin Lewis points us to this interesting paper by Jacob Westfall and Tal Yarkoni entitled, “Statistically Controlling for Confounding Constructs Is Harder than You Think.” Westfall and Yarkoni write: A common goal of statistical analysis in the social sciences is to draw inferences about the relative contributions of different variables to some outcome variable. When […] The post Problems with “incremental validity” or more generally in interpreting more than one…

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A small, underpowered treasure trove?

January 12, 2017
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A small, underpowered treasure trove?

Benjamin Kirkup writes: As you sometimes comment on such things; I’m forwarding you a journal editorial (in a society journal) that presents “lessons learned” from an associated research study. What caught my attention was the comment on the “notorious” design, the lack of “significant” results, and the “interesting data on nonsignificant associations.” Apparently, the work […] The post A small, underpowered treasure trove? appeared first on Statistical Modeling, Causal Inference,…

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When do stories work, Process tracing, and Connections between qualitative and quantitative research

January 11, 2017
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When do stories work, Process tracing, and Connections between qualitative and quantitative research

Jonathan Stray writes: I read your “when do stories work” paper (with Thomas Basbøll) with interest—as a journalist stories are of course central to my field. I wondered if you had encountered the “process tracing” literature in political science? It attempts to make sense of stories as “case studies” and there’s a nice logic of […] The post When do stories work, Process tracing, and Connections between qualitative and quantitative…

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We fiddle while Rome burns: p-value edition

January 7, 2017
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We fiddle while Rome burns:  p-value edition

Raghu Parthasarathy presents a wonderfully clear example of disastrous p-value-based reasoning that he saw in a conference presentation. Here’s Raghu: Consider, for example, some tumorous cells that we can treat with drugs 1 and 2, either alone or in combination. We can make measurements of growth under our various drug treatment conditions. Suppose our measurements […] The post We fiddle while Rome burns: p-value edition appeared first on Statistical Modeling,…

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“Which curve fitting model should I use?”

January 6, 2017
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“Which curve fitting model should I use?”

Oswaldo Melo writes: I have learned many of curve fitting models in the past, including their technical and mathematical details. Now I have been working on real-world problems and I face a great shortcoming: which method to use. As an example, I have to predict the demand of a product. I have a time series […] The post “Which curve fitting model should I use?” appeared first on Statistical Modeling,…

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When you add a predictor the model changes so it makes sense that the coefficients change too.

January 4, 2017
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Shane Littrell writes: I’ve recently graduated with my Masters in Science in Research Psych but I’m currently trying to get better at my stats knowledge (in psychology, we tend to learn a dumbed down, “Stats for Dummies” version of things). I’ve been reading about “suppressor effects” in regression recently and it got me curious about […] The post When you add a predictor the model changes so it makes sense…

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