SALARY SURVEY 2008
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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 2008. 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 predict salary—usually because they correlate strongly with other variables included in the model.
The survey sample of 1635 was selected in systematic, stratified fashion by KMPS and Readex Research from segments of MD&DI’s domestic circulation in the categories of finished medical device manufacturers and/or in vitro diagnostic manufacturers, representing 33,287 recipients at the time of sample selection.
Data were collected via mail survey from August 21 to October 2, 2008. The survey was closed for tabulation with 542 usable responses—a 33% response rate. As with any research, the results should be interpreted with the potential of nonresponse bias in mind. It is unknown how those who responded to the survey may be different from those who did not respond. In general, the higher the response rate, the lower the probability of estimation errors due to nonresponse and thus, the more stable the results. The margin of error for percentages based on smaller sample sizes will be larger.
The final results are based on the 460 individuals who indicated that they are involved in the industry and work full time in firms manufacturing finished medical devices and/or in vitro diagnostics, representing approximately 28,000 MD&DI recipients. The margin of error for percentages based on 460 usable responses is ±4.5% at the 95% confidence level. The margin of error for percentages based on smaller sample sizes will be larger.
