Readex Research can help your publication with all its research needs.  With over 55 years of publication research experience, we understand the challenges of the publishing industry.

Click here to learn more

Survey Details

Methodology

The survey sample of 1,453 was selected by Red 7 Media and Readex Research and included all Folio: subscribers classified as Editorial Management at the time of sample selection.

Data was collected via mail survey from April 10 to May 27, 2008.  The survey was closed for tabulation with 657 usable responses-a 45% response rate.  To ensure representation of the audience of interest, results have been filtered to include only the 598 respondents who indicated on the survey that they work full time and that their job functions are best described as editorial director or editor in chief; editor or executive editor; managing editor; or senior editor.

The margin of error for percentages based on all 598 respondents is ±3.0% at the 95% confidence level.

The Salary Calculator

The analysis of Folio:'s Editorial Management Salary Survey data used multiple regression analysis to model the determinants of salary by identifying those variables which, when taken together with appropriate weights, provide the best prediction of any individual’s actual salary.

The final salary prediction model is somewhat restricted in its applicability—it represents only full-time professionals who indicated their job functions are best described as editorial director or editor in chief, editor or executive editor, managing editor, or senior editor under 65 years old with salaries in the range of $25,000 to $210,000.

Statistically speaking, this model is moderately powerful: it explains 60% of the variation in salary (adjusted R-square = .607), and is significant by the F-test at p<.0000.

While a model explaining roughly 60% of the dependent variable's variation may be described as "moderately powerful," it still leaves about 40% of the variation unexplained.  It is virtually certain that other variables not captured through this survey also have an effect on salary levels: individual job performance, for example.  To the extent that this model does not include variables actually important in determining salary, its conclusions must be interpreted cautiously.