The information presented in this article provides a broad framework for approximating employee compensation in the U.S. medical device industry, based on MD&DI’s salary survey for 2007. Most of the responses analyzed are linear. Cross-tabulation is used to address one variable, such as job function, and analyze it simultaneously with a second variable, such as number of employees supervised. To account for the influence of additional variables, multivariate analysis is used to examine all variables simultaneously, account for their interdependence, and identify those that have the highest degree of predictive power. In any given year, some factors may not help to predict salary—usually because they correlate strongly with other variables included in the model.
The variables that were determined to have the greatest predictive value formed the basis for this year’s salary approximation worksheet. Statistically, the model is fairly powerful—it explains 61% of the salary variation (adjusted R-square = 0.502) and is significant by the F-test at p < 0.0005. Ninety-five percent of the time, its prediction around the mean is ± (standard error = $2054, mean = $102,474). Predictions tend to be most accurate for salary values in the middle of the range.
aIncludes AK, AZ, CA, CO, HI, ID, MT, NM, NV, OR, UT, WA, WY
The worksheet applies only to full-time professionals under the age of 65 in firms manufacturing medical devices or IVDs, with salaries ranging from $34,000 to $240,000, and for whom salary is at least 60% of the value of their total compensation package. The model provides a sense of the relative importance of each factor in predicting salary. It should not be used as a basis for comparison with any individual’s situation.
