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The SURVEYFREQ Procedure

Getting Started: SURVEYFREQ Procedure

The following example shows how you can use PROC SURVEYFREQ to analyze sample survey data. The example uses data from a customer satisfaction survey for a student information system (SIS), which is a software product that provides modules for student registration, class scheduling, attendance, grade reporting, and other functions.

The software company conducted a survey of school personnel who use the SIS. A probability sample of SIS users was selected from the study population, which included SIS users at middle schools and high schools in the three-state area of Georgia, South Carolina, and North Carolina. The sample design for this survey was a two-stage stratified design. A first-stage sample of schools was selected from the list of schools in the three-state area that use the SIS. The list of schools, or the first-stage sampling frame, was stratified by state and by customer status (whether the school was a new user of the system or a renewal user). Within the first-stage strata, schools were selected with probability proportional to size and with replacement, where the size measure was school enrollment. From each sample school, five staff members were randomly selected to complete the SIS satisfaction questionnaire. These staff members included three teachers and two administrators or guidance department members.

The SAS data set SIS_Survey contains the survey results, as well as the sample design information needed to analyze the data. This data set includes an observation for each school staff member responding to the survey. The variable Response contains the staff member’s response about overall satisfaction with the system.

The variable State contains the school’s state, and the variable NewUser contains the school’s customer status ('New Customer' or 'Renewal Customer'). These two variables determine the first-stage strata from which schools were selected. The variable School contains the school identification code and identifies the first-stage (primary) sampling units, or clusters. The variable SamplingWeight contains the overall sampling weight for each respondent. Overall sampling weights were computed from the selection probabilities at each stage of sampling and were adjusted for nonresponse.

Other variables in the data set SIS_Survey include SchoolType and Department. The variable SchoolType identifies the school as a high school or a middle school. The variable Department identifies the staff member as a teacher, or an administrator or guidance department member.

The following PROC SURVEYFREQ statements request a one-way frequency table for the variable Response:

   title 'Student Information System Survey';
   proc surveyfreq data=SIS_Survey;
      tables  Response;
      strata  State NewUser;
      cluster School;
      weight  SamplingWeight;
   run;

The PROC SURVEYFREQ statement invokes the procedure and identifies the input data set to be analyzed. The TABLES statement requests a one-way frequency table for the variable Response. The table request syntax for PROC SURVEYFREQ is very similar to the table request syntax for PROC FREQ. This example shows a request for a single one-way table, but you can also request two-way tables and multiway tables. As in PROC FREQ, you can request more than one table in the same TABLES statement, and you can use multiple TABLES statements in the same invocation of the procedure.

The STRATA, CLUSTER, and WEIGHT statements provide sample design information for the procedure, so that the analysis is done according to the sample design used for the survey, and the estimates apply to the study population. The STRATA statement names the variables State and NewUser, which identify the first-stage strata. Note that the design for this example also includes stratification at the second stage of selection (by type of school personnel), but you specify only the first-stage strata for PROC SURVEYFREQ. The CLUSTER statement names the variable School, which identifies the clusters or primary sample units (PSUs). The WEIGHT statement names the sampling weight variable.

Figure 83.1 and Figure 83.2 display the output produced by PROC SURVEYFREQ, which includes the "Data Summary" table and the one-way table, "Table of Response." The "Data Summary" table is produced by default unless you specify the NOSUMMARY option. This table shows there are 6 strata, 370 clusters or schools, and 1850 observations or respondents in the SIS_Survey data set. The sum of the sampling weights is approximately 39,000, which estimates the total number of school personnel in the study area that use the SIS.

Figure 83.1 SIS_Survey Data Summary
Student Information System Survey

The SURVEYFREQ Procedure

Data Summary
Number of Strata 6
Number of Clusters 370
Number of Observations 1850
Sum of Weights 38899.6482

Figure 83.2 displays the one-way table of Response, which provides estimates of the population total (weighted frequency) and the population percentage for each category, or level, of the variable Response. The response level 'Very Unsatisfied' has a frequency of 304, which means that 304 sample respondents fall into this category. It is estimated that 17.17% of all school personnel in the study population fall into this category, and the standard error of this estimate is 1.29%. Note that the estimates apply to the population of all SIS users in the study area, as opposed to describing only the sample of 1850 respondents. The estimate of the total number of school personnel that are 'Very Unsatisfied' is 6,678, with a standard deviation of 502. The standard errors computed by PROC SURVEYFREQ are based on the multistage stratified design of the survey. This differs from some of the traditional analysis procedures, which assume the design is simple random sampling from an infinite population.

Figure 83.2 One-Way Table of Response
Table of Response
Response Frequency Weighted
Frequency
Std Dev of
Wgt Freq
Percent Std Err of
Percent
Very Unsatisfied 304 6678 501.61039 17.1676 1.2872
Unsatisfied 326 6907 495.94101 17.7564 1.2712
Neutral 581 12291 617.20147 31.5965 1.5795
Satisfied 455 9309 572.27868 23.9311 1.4761
Very Satisfied 184 3714 370.66577 9.5483 0.9523
Total 1850 38900 129.85268 100.000  


The following PROC SURVEYFREQ statements request confidence limits for the percentages and a chi-square goodness-of-fit test for the one-way table of Response:

   proc surveyfreq data=SIS_Survey nosummary;
      tables  Response / cl nowt chisq;
      strata  State  NewUser;
      cluster School;
      weight  SamplingWeight;     
    run;

The NOSUMMARY option in the PROC statement suppresses the "Data Summary" table. In the TABLES statement, the CL option requests confidence limits for the percentages in the one-way table. The NOWT option suppresses display of the weighted frequencies and their standard deviations. The CHISQ option requests a Rao-Scott chi-square goodness-of-fit test.

Figure 83.3 shows the one-way table of Response, which includes confidence limits for the percentages. The 95% confidence limits for the percentage of users that are 'Very Unsatisfied' are 14.64% and 19.70%. To change the level of the confidence limits, which equals 5% by default, you can use the ALPHA= option. Like the other estimates and standard errors produced by PROC SURVEYFREQ, these confidence limit computations take into account the complex sample design of the survey, and the results apply to the entire study population.

Figure 83.3 Confidence Limits for Response Percentages
Student Information System Survey

The SURVEYFREQ Procedure

Table of Response
Response Frequency Percent Std Err of
Percent
95% Confidence Limits
for Percent
Very Unsatisfied 304 17.1676 1.2872 14.6364 19.6989
Unsatisfied 326 17.7564 1.2712 15.2566 20.2562
Neutral 581 31.5965 1.5795 28.4904 34.7026
Satisfied 455 23.9311 1.4761 21.0285 26.8338
Very Satisfied 184 9.5483 0.9523 7.6756 11.4210
Total 1850 100.000      

Figure 83.4 shows the chi-square goodness-of-fit results for the table of Response. The null hypothesis for this test is equal proportions for the levels of the one-way table. (To test a null hypothesis of specified proportions instead of equal proportions, you can use the TESTP= option to specify null hypothesis proportions.)


The chi-square test invoked by the CHISQ option is the Rao-Scott design-adjusted chi-square test, which takes the sample design into account and provides inferences for the entire study population. To produce the Rao-Scott chi-square statistic, PROC SURVEYFREQ first computes the usual Pearson chi-square statistic based on the weighted frequencies, and then adjusts this value with a design correction. An F approximation is also provided. For the table of Response, the F value is 30.0972 with a p-value of <0.0001, which indicates rejection of the null hypothesis of equal proportions for all response levels.

Figure 83.4 Chi-Square Goodness-of-Fit Test for Response
Rao-Scott Chi-Square Test
Pearson Chi-Square 251.8105
Design Correction 2.0916
   
Rao-Scott Chi-Square 120.3889
DF 4
Pr > ChiSq <.0001
   
F Value 30.0972
Num DF 4
Den DF 1456
Pr > F <.0001
Sample Size = 1850

Continuing to analyze the SIS_Survey data, the following PROC SURVEYFREQ statements request a two-way table of SchoolType by Response:

   proc surveyfreq data=SIS_Survey nosummary;
      tables  SchoolType * Response;
      strata  State NewUser;
      cluster School;
      weight  SamplingWeight;
   run;

The STRATA, CLUSTER, and WEIGHT statements do not change from the one-way table analysis, because the sample design and the input data set are the same. These SURVEYFREQ statements request a different table but specify the same sample design information.

Figure 83.5 shows the two-way table produced for SchoolType by Response. The first variable named in the two-way table request, SchoolType, is referred to as the row variable, and the second variable, Response, is referred to as the column variable. Two-way tables display all column variable levels for each row variable level. This two-way table lists all levels of the column variable Response for each level of the row variable SchoolType, 'Middle School' and 'High School'. Also SchoolType = 'Total' shows the distribution of Response overall for both types of schools. And Response = 'Total' provides totals over all levels of response, for each type of school and overall. To suppress these totals, you can specify the NOTOTAL option.

Figure 83.5 Two-Way Table of SchoolType by Response
Student Information System Survey

The SURVEYFREQ Procedure

Table of SchoolType by Response
SchoolType Response Frequency Weighted
Frequency
Std Dev of
Wgt Freq
Percent Std Err of
Percent
Middle School Very Unsatisfied 116 2496 351.43834 6.4155 0.9030
  Unsatisfied 109 2389 321.97957 6.1427 0.8283
  Neutral 234 4856 504.20553 12.4847 1.2953
  Satisfied 197 4064 443.71188 10.4467 1.1417
  Very Satisfied 94 1952 302.17144 5.0193 0.7758
  Total 750 15758 1000 40.5089 2.5691
High School Very Unsatisfied 188 4183 431.30589 10.7521 1.1076
  Unsatisfied 217 4518 446.31768 11.6137 1.1439
  Neutral 347 7434 574.17175 19.1119 1.4726
  Satisfied 258 5245 498.03221 13.4845 1.2823
  Very Satisfied 90 1762 255.67158 4.5290 0.6579
  Total 1100 23142 1003 59.4911 2.5691
Total Very Unsatisfied 304 6678 501.61039 17.1676 1.2872
  Unsatisfied 326 6907 495.94101 17.7564 1.2712
  Neutral 581 12291 617.20147 31.5965 1.5795
  Satisfied 455 9309 572.27868 23.9311 1.4761
  Very Satisfied 184 3714 370.66577 9.5483 0.9523
  Total 1850 38900 129.85268 100.000  

By default, without any other TABLES statement options, a two-way table displays the frequency, the weighted frequency and its standard deviation, and the percentage and its standard error for each table cell, or combination of row and column variable levels. But there are several options available to customize your table display by adding more information or by suppressing some of the default information.

The following PROC SURVEYFREQ statements request a two-way table of SchoolType by Response that displays row percentages, and also request a chi-square test of association between the two variables:

   proc surveyfreq data=SIS_Survey nosummary;
      tables  SchoolType * Response / row nowt chisq;
      strata  State NewUser;
      cluster School;
      weight  SamplingWeight;
   run;

The ROW option in the TABLES statement requests row percentages, which give the distribution of Response within each level of the row variable SchoolType. The NOWT option suppresses display of the weighted frequencies and their standard deviations. The CHISQ option requests a Rao-Scott chi-square test of association between SchoolType and Response.

Figure 83.6 displays the two-way table of SchoolType by Response. For middle schools, it is estimated that 25.79% of school personnel are satisfied with the student information system and 12.39% are very satisfied. For high schools, these estimates are 22.67% and 7.61%, respectively.

Figure 83.7 displays the chi-square test results. The Rao-Scott chi-square statistic equals 9.04, and the corresponding F value is 2.26 with a p-value of 0.0605. This indicates an association between school type (middle school or high school) and satisfaction with the student information system at the 10% significance level.

Figure 83.6 Two-Way Table with Row Percentages
Student Information System Survey

The SURVEYFREQ Procedure

Table of SchoolType by Response
SchoolType Response Frequency Percent Std Err of
Percent
Row
Percent
Std Err of
Row Percent
Middle School Very Unsatisfied 116 6.4155 0.9030 15.8373 1.9920
  Unsatisfied 109 6.1427 0.8283 15.1638 1.8140
  Neutral 234 12.4847 1.2953 30.8196 2.5173
  Satisfied 197 10.4467 1.1417 25.7886 2.2947
  Very Satisfied 94 5.0193 0.7758 12.3907 1.7449
  Total 750 40.5089 2.5691 100.000  
High School Very Unsatisfied 188 10.7521 1.1076 18.0735 1.6881
  Unsatisfied 217 11.6137 1.1439 19.5218 1.7280
  Neutral 347 19.1119 1.4726 32.1255 2.0490
  Satisfied 258 13.4845 1.2823 22.6663 1.9240
  Very Satisfied 90 4.5290 0.6579 7.6128 1.0557
  Total 1100 59.4911 2.5691 100.000  
Total Very Unsatisfied 304 17.1676 1.2872    
  Unsatisfied 326 17.7564 1.2712    
  Neutral 581 31.5965 1.5795    
  Satisfied 455 23.9311 1.4761    
  Very Satisfied 184 9.5483 0.9523    
  Total 1850 100.000      

Figure 83.7 Chi-Square Test of No Association
Rao-Scott Chi-Square Test
Pearson Chi-Square 18.7829
Design Correction 2.0766
   
Rao-Scott Chi-Square 9.0450
DF 4
Pr > ChiSq 0.0600
   
F Value 2.2613
Num DF 4
Den DF 1456
Pr > F 0.0605
Sample Size = 1850

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