Article in journal


No cake for spunky
I am reading articles on statistics at work a lot and I found this one - which rather bemused me. Because it dealt with medical journals where you would expect high level expertise.

P value, odds ratio,and 95% confidence interval for coefficients in MLR was reported in 75.2% and sufficient cases (>10) percovariate of limiting sample size were reported in the 58.7% of the articles. No article reported the test for conformity of linear gradient for continuous covariates. Total score was not significantly different across the journals.
I am not familiar with the later statistic, but on a whole that seems a rather low floor to get over. Remarkable that these were not reported in the other quarter of the articles.

However, involvement of statistician or epidemiologist as a co‑author improved the average quality score significantly (P=0.014).
It is encouraging to know when they asked professional statisticians to participate the statistics got better.:yup:

Conclusions: Reporting of MLR in many Indian journals is incomplete. Only one
article managed to score 8 out of 10 among 109 articles under review. All others scored less.
Its a bit scary that the quality was that low in medical journals in India in 2011 (more likely the previous decade). I have not yet found the scale they used to measure quality, perhaps it was very high. But previous findings in US medical journals for logistic regression generated similar concerning findings.

A recent study conducted on 196 original articles published in two Indian pharmacology journals between 2002 and 2010 found that only
22% reported appropriate descriptive statistics. Only two out of 196 articles mentioned about the assumptions related to the
statistical method applied, and 69.3% articles used appropriatestatistical methods.[1]
Which means 30 percent did not use appropriate journals where you would think the statisics would be rather precise :(
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No cake for spunky
These are the critier if any are interested for quality (they don't seem very high).

These 10 criteria are (i) sufficient cases (>10) per covariate, (ii) conformity of linear gradient for continuous variables, (iii)
testing of interactions, (iv) testing of collinearity, (v) validation of model, (vi) P value, odds ratio, and 95% confidence interval of odds ratio, (vii) selection of potential covariates, (viii) coding of covariates, (ix) goodness‑of‑fit or classification summary, and (x) model fitting procedure

I wonder if "conformity of linear gradient for continuous variables" means they were tested for linearity. Notice there is no requirement that they be tested for outliers or highly leveraged points.


TS Contributor
if you read German, the book " Der Hund der Eier legt" has plenty of examples from european medical journals, from the 90-ties. No reason to expect an improvement unfortunately.

The title means "the egg-laying dog" BTW.



TS Contributor
These 10 criteria are (i) sufficient cases (>10) per covariate,
But rules of thumb for logistic regression do not refer to number of cases,
but to number of cases in the smaller outcome group?!

With kind regards