An example follows of a survey method section that illustrates many of the steps just mentioned. This excerpt (used with permission) comes from a journal article reporting a study of factors affecting student attrition in one small liberal arts college (Bean & Creswell, 1980 , pp. 321–322).
Methodology
The site of this study was a small (enrollment 1,000), religious, coeducational, liberal arts college in a Midwestern city with a population of 175,000 people. [Authors identified the research site and population.]
The dropout rate the previous year was 25%. Dropout rates tend to be highest among freshmen and sophomores, so an attempt was made to reach as many freshmen and sophomores as possible by distribution of the questionnaire through classes. Research on attrition indicates that males and females drop out of college for different reasons (Bean, 1978, in press; Spady, 1971). Therefore, only women were analyzed in this study.
During April 1979, 169 women returned questionnaires. A homogeneous sample of 135 women who were 25 years old or younger, unmarried, full-time U.S. citizens, and Caucasian was selected for this analysis to exclude some possible confounding variables (Kerlinger, 1973).
Of these women, 71 were freshmen, 55 were sophomores, and 9 were juniors. Of the students, 95% were between the ages of 18 and 21. This sample is biased toward higher-ability students as indicated by scores on the ACT test. [Authors presented descriptive information about the sample.]
Data were collected by means of a questionnaire containing 116 items. The majority of these were Likert-like items based on a scale from “a very small extent” to “a very great extent.” Other questions asked for factual information, such as ACT scores, high school grades, and parents’ educational level. All information used in this analysis was derived from questionnaire data. This questionnaire had been developed and tested at three other institutions before its use at this college. [Authors discussed the instrument.]
Concurrent and convergent validity (Campbell & Fiske, 1959 ) of these measures was established through factor analysis, and was found to be at an adequate level. Reliability of the factors was established through the coefficient alpha. The constructs were represented by 25 measures—multiple items combined on the basis of factor analysis to make indices—and 27 measures were single item indicators. [Validity and reliability were addressed.]
Multiple regression and path analysis (Heise, 1969; Kerlinger & Pedhazur, 1973) were used to analyze the data. In the causal model …, intent to leave was regressed on all variables which preceded it in the causal sequence. Intervening variables significantly related to intent to leave were then regressed on organizational variables, personal variables, environmental variables, and background variables. [Data analysis steps were presented.]
Table 8.1 A Checklist of Questions for Designing a Survey Method
| __________ | Is the purpose of a survey design stated? |
| __________ | Are the reasons for choosing the design mentioned? |
| __________ | Is the nature of the survey (cross-sectional vs. longitudinal) identified? |
| __________ | Is the population and its size mentioned? |
| __________ | Will the population be stratified? If so, how? |
| __________ | How many people will be in the sample? On what basis was this size chosen? |
| __________ | What will be the procedure for sampling these individuals (e.g., random, nonrandom)? |
| __________ | What instrument will be used in the survey? Who developed the instrument? |
| __________ | What are the content areas addressed in the survey? The scales? |
| __________ | What procedure will be used to pilot or field-test the survey? |
| __________ | What is the timeline for administering the survey? |
| __________ | What are the variables in the study? |
| __________ | How do these variables cross-reference with the research questions and items on the survey? |
| What specific steps will be taken in data analysis to do the following: | |
| (a)_______ | Analyze returns? |
| (b)_______ | Check for response bias? |
| (c)_______ | Conduct a descriptive analysis? |
| (d)_______ | Collapse items into scales? |
| (e)_______ | Check for reliability of scales? |
| (f)_______ | Run inferential statistics to answer the research questions or assess practical implications of the results? |
| _______ | How will the results be interpreted? |