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 2001. Most of the responses analyzed are linear. They use cross-tabulation to compare 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 only moderately powerful—it explains a little more than 61% of the salary variation (adjusted R-square = 0.635) and is significant by the F-test at p<0.001. About one-third of the time, predictions of individual salaries will be off by 25% or more from actual values. Predictions tend to be most accurate for salary values in the middle of the range.
Note: The worksheet applies only to full-time employees in firms manufacturing medical devices or in vitro diagnostics, with salaries ranging from $30,000 to $170,000. 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.
