# Statistics

The old adage of “Lies, Damned Lies and Statistics” may be true, but I [like] to believe it has more to do with a lack of knowledge and competence than premeditation. Here is what I have learned so far in my quest to avoid spreading “damned lies”.

## Scientific writing: “The C-word: Scientific euphemisms do not improve causal inference from observational data”

One of the first things taught in statistics, is that correlation does not imply causation. Indeed, to say something about causation, one basically needs experimental or quasi-experimental design. Unfortunately, this can be difficult, or impossible in many contexts....

read more## Moderation and Mediation analysis

Just a course in Mediation and Moderation analysis, and the use of the Process macro, with Amanda Montoya. Brilliant, in that it really explains how to use the tool, and how to interpret the results. Amanda is also a gifted instructor. 🙂 Here a few notes and...

read more## Graphs and diagrams..

I am continuously amazed at some of the statistics and associated graphs I see in published research. One recent example I saw caught my interest first, when I saw the legend for the stars indicating significance levels.Traditionally, one star is for 0.10; (IF you...

read more## SNA measures are not like other measures

There is a multitude of measures in social network analysis (SNA). In other social sciences, great lengths are gone to develop robust and valid measures, with discrete validity, which means there are relatively few overlapping constructs; and some remain standard for...

read more## What topics does your favorite journal publish?

Another day, another use for bibliometric analysis. I was recently at a conference where the editor of AMJ strongly recommended to read the mission statement of a journal before submitting; hitting the target is key to get it considered, and published. There is no...

read more## Publishing in top tier outlets: some insights from bibliometric analysis

I was discussing with a friend what it takes to get published in the very top journals. The established answers include: need excellent data (eg. multiple sources and time points), a novel and interesting idea, and well written work. . . Is this really it? I think...

read more## Cohen’s d explained

Great page with a simple and visual explaination of what Cohen's d is, and how to make sense of it. http://rpsychologist.com/d3/cohend/

read more## Fit Statistics in Structural Equation Modeling

Nice summary of what fit statistics are http://www.deeplytrivial.com/2018/04/statistics-sunday-fit-statistics-in.html?m=1

read more## P-hacking

## Heteroskedasity.. and a good statistics blog

There are many terms in statistics one should know, and most courses assumes one does.. Further, many statistics text books explain these terms mathematically, and in such a way I do not find it conducive to understanding 🙂 the Blog Deeply Trivial covers quite a few...

read more## The ongoing P-value debate

There are ever more good articles on what p-values are, their use and abuse.. as well as alternatives. Two I have come over today include on article outlining the issue from a journalistic view, showing arguments for and against (in VOX); the second a journal articel...

read more## What is a “Meta Analysis”

Meta analysis' are often considered the gold standard for studies; a single study is never conclusive due to potential errors in design or data, whereas when results from many studies are systematically analyzed, they can be. Here is a YouTube series that goes through...

read more## Endogeneity… What it is, and potential sources

Endogeneity has received attention in the past decade, as a significant source of bias in results reported in a wide variety of studies. Papers can now be desk rejected by top journals if there is reason to believe there may be endogeneity at play. Endogeneity refers...

read more## Some may enjoy reading this..

..and spend a couple of minutes studying the graph. A graph showing what people think of when using unspecific terms like: "some", "a few", "many", as well as various types of probabilities. Rather interesting.. as well as a short discussion on what to do with...

read more## The futuRe of statistics.. is R…

It is the most up to date software; it will make you more attractive on the job market; and enable you to do any analysis from one program. The two (linked) articles explain why, and give a great list of resources for how to learn, including Coursera : Read more at:...

read more## The natural selection of bad science

This paper lays out the argument that flawed research design, methods and analysis (all be it unintentional) will yield results in greater volume and that are more novel and surprising; and thus, also greater rate of publishing. As publishing is a key factor in...

read more## Measurement error and the replication crisis

A common assumption has been that if one finds statistically significant results with noisy data, it means that the findings are conservative. (The intuition is that had there not been strong associations present, they would not have made it through the noise) In...

read more## How statistics lost their power

Interesting historical perspective, and why statistics as a tool to form policy and public opinion may loose its effect in the time to come. some points: the nation is a misleading entity to use; while some cities flourish and grow, other regions are hit hard; an...

read more## Type 1 Vs type 2 errors

http://daniellakens.blogspot.no/2016/12/why-type-1-errors-are-more-important.html?m=1

read more## Statistics tools

Some times, one needs to calculate some statistics, like effect size; not complex, but takes time. Here is a collection of tools to make that easier. http://www.danielsoper.com/statcalc/

read more## What happened in the US election? What should we learn from it as researchers?

The US election result came as a big surprise to me; as to most who have put their faith in polling and statistical analysis predicting the outcome. Nate Silver and his company FiveThirtyEight is widely acknowledged to have some of the best analysis in the business;...

read more## Nate Silver / Fivethirtyeight and high level polling

This, and other articles on the site offer great examples of real world sampling issues, problems and solutions. nice addendum to theoretical methodology. (and just how much it matters!) ...

read more## A great guide for how to lie with statistics: (and how to spot when it is done)

While I feel sure academics have far more tricks up their sleeves (like fishing and p-hacking) politicians are are a creative bunch. Here is an article by a Cambridge professor on nine favored strategies. In short, they are: Use real number, but change its meaning...

read more## What statistical software to learn?

There are a range of statistical software packages available, some costly, other free, and some in between. Which to choose? Which to invest time to learn (Blood sweat, tears and frustration) and money to buy? SPSS has it forte in that it has a pretty interface that...

read more## How politicians poisoned statistics

In this article, Tim Harford uses the distinction put forth by the Princeton philosopher Harry Frankfurt, between those who lie with statistics, and those who simply do not care what the facts are, but use statistics to support their position. The latter can be...

read more## Type 1 and Type 2 errors… what they are..

Great with visuals to really understand a concept 🙂

read more## Randomized control trial: The gold standard or overrated?

While randomized control trial (RCT) have long been seen as the epitome of evidence based research, having served to modernize the field of medicine, this article questions its use to test social policy. The argument is that where RCT's come into their own when...

read more## How well do you see a correlation?

We have all read correlation matrixes, and have seen: As a rule of thumb, the following guidelines on strength of relationship are often useful (though many experts would somewhat disagree on the choice of boundaries). Value of r Strength of relationship 1.0 to -0.5...

read more## Intro Statistics 9 Dance of the p Values

I use pictures from the ESCI software to give a brief, easy account of the Dance of the p Values. The simulation illustrates how enormously and disastrously variable the p value is, simply because of sampling variability. Never trust a p value! Use estimation, not NHST!

## The dance of the p-values

Criticizing the use of p-values has begun to be so common place that it is getting dull repeating it. However, in his class on Moderation and Mediation today, Dominique Muller recommended a YouTube presentation called: “The dance of the P-values”. It puts the...

read more## The rater in surveys as a source of bias.

As a method of collecting data, surveys have been widely criticized for the biases that are included in the data. When the source of biases are the same for both the dependent and the independent variable, (as in, what is used to explain, and what we are seeking to...

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