Use of a path model to analyze factors that influence hospital pharmacists' salaries.
The direct and indirect effects of eight factors on Texas hospital pharmacists' salaries are described. Data for a path analysis (a method of examining relationships among specific variables while controlling for the effects of other variables) were collected by mail survey during the fall of 1985 from randomly selected hospital pharmacists residing in Texas. A path model was constructed to examine the effects of the following variables on the annual salary earned by full-time pharmacists: position, gender, seniority, academic degree, age, number of hours worked per week, size of hospital, and location of hospital. The relationships among the variables were evaluated using linear regression analysis. Of 1500 questionnaires mailed, 502 usable responses from full-time pharmacists were received. Six factors--gender, position, seniority, size of hospital, academic degree, and number of hours worked per week--had significant direct impact on financial compensation. Pharmacists' position also had an indirect effect on salary through the number of hours worked per week, with managers working more hours than nonmanagers. Position was influenced by seniority, gender, size of hospital, and academic degree. Male pharmacists earned more than their female counterparts. Age and hospital location had no significant influence on annual salary, position, or the number of hours worked per week. Overall, path analysis showed only 11 of 21 relationships among the nine variables to be significant. Seniority, gender, size of hospital, academic degree, position, and number of hours worked per week all had a significant effect on salary.
Shepherd
M D
MD
Pharmacy Administration Division, College of Pharmacy, University of Texas, Austin 78712-1074.
Pongcharoensuk
P
P
Sullivan
S D
SD
D003625:Data Collection; D004512:Education, Pharmacy; D015233:Models, Statistical; D010595:Pharmacists / Q000191:economics*; D010607:Pharmacy Service, Hospital / Q000191:economics*; D012456:Salaries and Fringe Benefits / Q000706:statistics & numerical data*; D013781:Texas