Running an Existing Sample Plan. 21 CSPLAN and CSSELECT Commands Additional Features. 21
Preparing a Complex Sample for Analysis
Creating a New Analysis Plan. 24 Analysis Preparation Wizard: Design Variables. 25 Tree Controls for Navigating the Analysis Wizard. 26 Analysis Preparation Wizard: Estimation Method. 27 Analysis Preparation Wizard: Size. 28 Define Unequal Sizes. 29 Analysis Preparation Wizard: Stage Summary. 30 Analysis Preparation Wizard: Finish. 31 Modifying an Existing Analysis Plan. 32 Analysis Preparation Wizard: Plan Summary. 33
Complex Samples Plan Complex Samples Frequencies
Complex Samples Frequencies Statistics. 39 Complex Samples Missing Values. 40 Complex Samples Options. 41
Complex Samples Descriptives
Complex Samples Descriptives Statistics. 45 Complex Samples Descriptives Missing Values. 46 Complex Samples Options. 46
Complex Samples Crosstabs
Complex Samples Crosstabs Statistics. 51 Complex Samples Missing Values. 53 Complex Samples Options. 53

Complex Samples Ratios

Complex Samples Ratios Statistics. 57 Complex Samples Ratios Missing Values. 58 Complex Samples Options. 58
Complex Samples General Linear Model
Complex Samples General Linear Model Statistics. 65 Complex Samples Hypothesis Tests. 66 Complex Samples General Linear Model Estimated Means. 68 Complex Samples General Linear Model Save. 69 Complex Samples General Linear Model Options. 70 CSGLM Command Additional Features. 71
10 Complex Samples Logistic Regression
Complex Samples Logistic Regression Reference Category. 75 Complex Samples Logistic Regression Model. 76 Complex Samples Logistic Regression Statistics. 78 Complex Samples Hypothesis Tests. 80 Complex Samples Logistic Regression Odds Ratios. 81 Complex Samples Logistic Regression Save. 83 Complex Samples Logistic Regression Options. 84 CSLOGISTIC Command Additional Features. 85
Part II: Examples 11 Complex Samples Sampling Wizard
Using the Wizard. Plan Summary. Sampling Summary. Sample Results. Obtaining a Sample from a Partial Sampling Frame...

. 89. 121

Obtaining a Sample from a Full Sampling Frame. 89
Using the Wizard to Sample from the First Partial Frame. Sample Results. Using the Wizard to Sample from the Second Partial Frame. Sample Results. Related Procedures.
12 Complex Samples Analysis Preparation Wizard
Using the Complex Samples Analysis Preparation Wizard to Ready NHIS Public Data. 123 Using the Wizard. 123 Summary. 126 Preparing for Analysis When Sampling Weights Are Not in the Data File. 126 Computing Inclusion Probabilities and Sampling Weights Using the Wizard. Summary. Related Procedures. 137 137
13 Complex Samples Frequencies
Using Complex Samples Frequencies to Analyze Nutritional Supplement Usage. 139 Running the Analysis. Frequency Table. Frequency by Subpopulation. Summary. Related Procedures.... 144

14 Complex Samples Descriptives
Using Complex Samples Descriptives to Analyze Activity Levels. 145 Running the Analysis. 145 Univariate Statistics. 148
Univariate Statistics by Subpopulation. 149 Summary. 150 Related Procedures. 150
15 Complex Samples Crosstabs
Using Complex Samples Crosstabs to Measure the Relative Risk of an Event. 151 Running the Analysis. Crosstabulation. Risk Estimate. Risk Estimate by Subpopulation. Summary. Related Procedures.... 157 158
16 Complex Samples Ratios
Running the Analysis. Ratios. Pivoted Ratios Table. Summary. Related Procedures....
Using Complex Samples Ratios to Aid Property Value Assessment. 159
17 Complex Samples General Linear Model
Using Complex Samples General Linear Model to Fit a Two-Factor ANOVA 167 Running the Analysis. 167 Model Summary. 172
Tests of Model Effects. Parameter Estimates. Estimated Marginal Means. Summary. Related Procedures.
18 Complex Samples Logistic Regression
Running the Analysis. Pseudo R-Squares. Classification. Tests of Model Effects. Parameter Estimates. Odds Ratios. Summary. Related Procedures......

.. 192 192

Using Complex Samples Logistic Regression to Assess Credit Risk. 181

Bibliography Index

193 195

Part 1: User's Guide

Chapter
Introduction to SPSS Complex Samples Procedures
An inherent assumption of analytical procedures in traditional software packages is that the observations in a data file represent a simple random sample from the population of interest. This assumption is untenable for an increasing number of companies and researchers who find it both cost-effective and convenient to obtain samples in a more structured way. The SPSS Complex Samples option allows you to select a sample according to a complex design and incorporate the design specifications into the data analysis, thus ensuring that your results are valid.
Properties of Complex Samples
A complex sample can differ from a simple random sample in many ways. In a simple random sample, individual sampling units are selected at random with equal probability and without replacement (WOR) directly from the entire population. By contrast, a given complex sample can have some or all of the following features:
Stratification. Stratified sampling involves selecting samples independently within
non-overlapping subgroups of the population, or strata. For example, strata may be socioeconomic groups, job categories, age groups, or ethnic groups. With stratification, you can ensure adequate sample sizes for subgroups of interest, improve the precision of overall estimates, and use different sampling methods from stratum to stratum.

PPS Murthy. This is a first-stage method that selects two clusters from each
PPS Sampford. This is a first-stage method that selects more than two clusters
from each stratum with probability proportional to cluster size and without replacement. It is an extension of Brewers method. A cluster variable must be specified to use this method.
Use WR estimation for analysis. By default, an estimation method is specified in
the plan file that is consistent with the selected sampling method. This allows you to use with-replacement estimation even if the sampling method implies WOR estimation. This option is available only in stage 1.
Measure of Size (MOS). If a PPS method is selected, you must specify a measure of
size that defines the size of each unit. These sizes can be explicitly defined in a variable or they can be computed from the data. Optionally, you can set lower and upper bounds on the MOS, overriding any values found in the MOS variable or computed from the data. These options are available only in stage 1.
11 Sampling from a Complex Design
Sampling Wizard: Sample Size
Figure 2-4 Sampling Wizard, Sample Size step
This step allows you to specify the number or proportion of units to sample within the current stage. The sample size can be fixed or it can vary across strata. For the purpose of specifying sample size, clusters chosen in previous stages can be used to define strata.
Units. You can specify an exact sample size or a proportion of units to sample. Value. A single value is applied to all strata. If Counts is selected as the unit
metric, you should enter a positive integer. If Proportions is selected, you should enter a non-negative value. Unless sampling with replacement, proportion values should also be no greater than 1.

12 Chapter 2

Unequal values for strata. Allows you to enter size values on a per-stratum basis
via the Define Unequal Sizes dialog box.
Read values from variable. Allows you to select a numeric variable that contains
size values for strata. If Proportions is selected, you have the option to set lower and upper bounds on the number of units sampled.

Define Unequal Sizes

Figure 2-5 Define Unequal Sizes dialog box
The Define Unequal Sizes dialog box allows you to enter sizes on a per-stratum basis.
Size Specifications grid. The grid displays the cross-classifications of up to five strata
or cluster variablesone stratum/cluster combination per row. Eligible grid variables include all stratification variables from the current and previous stages and all cluster variables from previous stages. Variables can be reordered within the grid or moved to the Exclude list. Enter sizes in the rightmost column. Click Labels or Values to toggle the display of value labels and data values for stratification and cluster variables in the grid cells. Cells that contain unlabeled values always show values.

Modifying an Existing Sample Plan
E From the menus choose: Analyze Complex Samples Select a Sample. E Select Edit a sample design and choose a plan file to edit. E Click Next to continue through the Wizard. E Review the sampling plan in the Plan Summary step, and then click Next.
Subsequent steps are largely the same as for a new design. See the Help for individual steps for more information.
E Navigate to the Finish step, and specify a new name for the edited plan file or choose
to overwrite the existing plan file. Optionally, you can: Specify stages that have already been sampled. Remove stages from the plan.

20 Chapter 2

Figure 2-11 Sampling Wizard, Plan Summary step
This step allows you to review the sampling plan and indicate stages that have already been sampled. If editing a plan, you can also remove stages from the plan.
Previously sampled stages. If an extended sampling frame is not available, you will have to execute a multistage sampling design one stage at a time. Select which stages have already been sampled from the drop-down list. Any stages that have been executed are locked; they are not available in the Draw Sample Selection Options step, and they cannot be altered when editing a plan. Remove stages. You can remove stages 2 and 3 from a multistage design.
21 Sampling from a Complex Design
Running an Existing Sample Plan
E From the menus choose: Analyze Complex Samples Select a Sample. E Select Draw a sample and choose a plan file to run. E Click Next to continue through the Wizard. E Review the sampling plan in the Plan Summary step, and then click Next. E The individual steps containing stage information are skipped when executing a
sample plan. You can now go on to the Finish step at any time. Optionally, you can: Specify stages that have already been sampled.
CSPLAN and CSSELECT Commands Additional Features
The SPSS command language also allows you to: Specify custom names for output variables. Control the output in the Viewer. For example, you can suppress the stagewise summary of the plan that is displayed if a sample is designed or modified, suppress the summary of the distribution of sampled cases by strata that is shown if the sample design is executed, and request a case processing summary. Choose a subset of variables in the working data file to write to an external sample file. See the SPSS Command Syntax Reference for complete syntax information.

were sampled.

29 Preparing a Complex Sample for Analysis
Value. A single value is applied to all strata. If Population Sizes is selected as the
unit metric, you should enter a non-negative integer. If Inclusion Probabilities is selected, you should enter a value between 0 and 1, inclusive.

size values for strata.

Figure 3-5 Define Unequal Sizes dialog box

30 Chapter 3

Analysis Preparation Wizard: Stage Summary
Figure 3-6 Analysis Preparation Wizard, Plan Summary step (stage 1)
This is the last step within each stage, providing a summary of the analysis design specifications through the current stage. From here, you can either proceed to the next stage (creating it if necessary) or save the analysis specifications. If you cannot add another stage, it is likely because: No cluster variable was specified in the Design Variables step.
31 Preparing a Complex Sample for Analysis
You selected WR estimation in the Estimation Method step. This is the third stage of the analysis, and the Wizard supports a maximum of three stages.
Analysis Preparation Wizard: Finish
Figure 3-7 Analysis Preparation Wizard, Finish step
This is the final step. You can save the plan file now or paste your selections to a syntax window. When making changes to stages in the existing plan file, you can save the edited plan to a new file or overwrite the existing file. When adding stages without making changes to existing stages, the Wizard automatically overwrites the existing plan file. If you want to save the plan to a new file, choose to Paste the syntax generated by the Wizard into a syntax window and change the filename in the syntax commands.

32 Chapter 3

Modifying an Existing Analysis Plan
E From the menus choose: Analyze Complex Samples Prepare for Analysis. E Select Edit a plan file, and choose a plan filename to which you will save the analysis
E Click Next to continue through the Wizard. E Review the analysis plan in the Plan Summary step, and then click Next.
Subsequent steps are largely the same as for a new design. For more information, see the Help for individual steps.
E Navigate to the Finish step, and specify a new name for the edited plan file, or choose
to overwrite the existing plan file. Optionally, you can: Remove stages from the plan.

Example. Using the Complex Samples Descriptives procedure, you can obtain
univariate descriptive statistics for the activity levels of U.S. citizens based on the results of the National Health Interview Survey (NHIS) and with an appropriate analysis plan for this public use data.
Statistics. The procedure produces means and sums, plus t tests, standard errors,
confidence intervals, coefficients of variation, unweighted counts, population sizes, design effects, and square roots of design effects for each estimate.
Data. Measures should be scale variables. Subpopulation variables can be string
or numeric but should be categorical.
Obtaining Complex Samples Descriptives
E From the menus choose: Analyze Complex Samples Descriptives. E Select a plan file, and optionally select a custom joint probabilities file. E Click Continue.
44 Chapter 6 Figure 6-1 Descriptives dialog box
E Select at least one measure variable.
45 Complex Samples Descriptives
Complex Samples Descriptives Statistics
Figure 6-2 Descriptives Statistics dialog box
Summaries. This group allows you to request estimates of the means and sums of the measure variables. Additionally, you can request t tests of the estimates against a specified value. Statistics. This group produces statistics associated with the mean or sum. Standard error. The standard error of the estimate. Confidence interval. A confidence interval for the estimate, using the specified
Unweighted count. The number of units used to compute the estimate. Population size. The estimated number of units in the population. Design effect. The ratio of the variance of the estimate to the variance obtained

46 Chapter 6

Complex Samples Descriptives Missing Values
Figure 6-3 Descriptives Missing Values dialog box
Statistics for Measure Variables. This group determines which cases are used in the

analysis.

Use all available data. Missing values are determined on a variable-by-variable

CSLOGISTIC Command Additional Features
The SPSS command language also allows you to: Specify custom tests of effects versus a linear combination of effects or a value (using the CUSTOM subcommand). Fix values of other model variables when computing odds ratios for factors and covariates (using the ODDSRATIOS subcommand). Specify a tolerance value for checking singularity (using the CRITERIA subcommand).

86 Chapter 10

Create user-specified names for saved variables (using the SAVE subcommand). Produce a general estimable function table (using the PRINT subcommand). See the SPSS Command Syntax Reference for complete syntax information.

Part 2: Examples

Complex Samples Sampling Wizard
Obtaining a Sample from a Full Sampling Frame
A state agency is charged with ensuring fair property taxes from county to county. Taxes are based on the appraised value of the property, so the agency wants to survey a sample of properties by county to be sure that each countys records are equally up-to-date. However, resources for obtaining current appraisals are limited, so its important that what is available is used wisely. The agency decides to employ complex sampling methodology to select a sample of properties. A listing of properties is collected in property_assess_cs.sav, found in the \tutorial\sample_files\ subdirectory of the directory in which you installed SPSS. Use the Complex Samples Sampling Wizard to select a sample.

Using the Wizard

E To run the Complex Samples Sampling Wizard, from the menus choose: Analyze Complex Samples Select a Sample.
90 Chapter 11 Figure 11-1 Sampling Wizard, Welcome step
E Select Design a sample and type c:\property_assess.csplan as the name of the plan

E Click Next.

91 Complex Samples Sampling Wizard Figure 11-2 Sampling Wizard, Design Variables step (stage 1)
E Select County as a stratification variable. E Select Township as a cluster variable. E Click Next, and then click Next in the Method step.
This design structure means that independent samples are drawn for each county. In this stage, townships are drawn as the primary sampling unit using the default method, simple random sampling.
92 Chapter 11 Figure 11-3 Sampling Wizard, Sample Size step (stage 1)
E Type 4 as the value for the number of clusters to select in this stage. E Click Next, and then click Next in the Output Variables step.
93 Complex Samples Sampling Wizard Figure 11-4 Sampling Wizard, Plan Summary step (stage 1)
E Select Yes, add stage 2 now. E Click Next.
94 Chapter 11 Figure 11-5 Sampling Wizard, Design Variables step (stage 2)
E Select Neighborhood as a stratification variable. E Click Next, and then click Next in the Method step.
This design structure means that independent samples are drawn for each neighborhood of the townships drawn in stage 1. In this stage, properties are drawn as the primary sampling unit using simple random sampling.

110 Chapter 11 Figure 11-20 Sampling Wizard, Plan Summary step (stage 2)
111 Complex Samples Sampling Wizard Figure 11-21 Sampling Wizard, Draw Sample, Selection Options step
E Select Custom value for the type of random seed to use, and type 241972 as the value.
112 Chapter 11 Figure 11-22 Sampling Wizard, Finish step
These selections produce the sampling plan file demo_1.csplan and draw a sample according to that plan.
113 Complex Samples Sampling Wizard
Figure 11-23 Data Editor with sample results
You can see the sampling results in the Data Editor. Five new variables were saved to the working file, representing the inclusion probabilities and cumulative sampling weights for each stage, plus the final sampling weights for the first two stages. Cities with values for these variables were selected to the sample. Cities with system-missing values for the variables were not selected. For each city selected, the company acquired subdivision and household unit information and placed it in demo_cs_2.sav. Use this file and the Sampling Wizard to sample the third stage of this design.

114 Chapter 11

Using the Wizard to Sample from the Second Partial Frame
E To run the Complex Samples Sampling Wizard, from the menus choose: Analyze Complex Samples Select a Sample. Figure 11-24 Sampling Wizard, Welcome step
E Select Design a sample and type c:\demo_2.csplan as the name of the plan file. E Click Next.
115 Complex Samples Sampling Wizard Figure 11-25 Sampling Wizard, Design Variables step (stage 1)
E Select Subdivision as a stratification variable. E Select Cumulative Sampling Weight for Stage 2 as the input sample weight variable. E Click Next, and then click Next in the Method step.
This design structure means that independent samples are drawn for each subdivision. In this stage, household units are drawn as the primary sampling unit using the default method, simple random sampling.
116 Chapter 11 Figure 11-26 Sampling Wizard, Sample Size step (stage 1)
E Type 0.2 as the value for the proportion of units to select in this stage. E Click Next, and then click Next in the Output Variables step.
117 Complex Samples Sampling Wizard Figure 11-27 Sampling Wizard, Plan Summary step (stage 1)
118 Chapter 11 Figure 11-28 Sampling Wizard, Draw Sample, Selection Options step

E Browse to the \tutorial\sample_files\ subdirectory of the directory in which you
installed SPSS and select nhis2000_subset.csaplan.

E Click Continue.

141 Complex Samples Frequencies Figure 13-2 Frequencies dialog box
E Select Vitamin/mineral supplmnts-past 12 m as a frequency variable. E Select Age category as a subpopulation variable. E Click Statistics.
142 Chapter 13 Figure 13-3 Frequencies Statistics dialog box
E Select Table percent in the Cells group. E Select Confidence interval in the Statistics group. E Click Continue. E Click OK in the Frequencies dialog box.

Frequency Table

Figure 13-4 Frequency table for variable/situation
143 Complex Samples Frequencies
Each selected statistic is computed for each selected cell measure. The first column contains estimates of the number and percentage of the population that do or do not take vitamin/mineral supplements. The confidence intervals are non-overlapping; thus, you can conclude that, overall, more Americans take vitamin/mineral supplements than not.
Frequency by Subpopulation
Figure 13-5 Frequency table by subpopulation
When computing statistics by subpopulation, each selected statistic is computed for each selected cell measure by value of Age category. The first column contains estimates of the number and percentage of the population of each category that do or do not take vitamin/mineral supplements. The confidence intervals for the table

144 Chapter 13

percentages are all non-overlapping; thus, you can conclude that with increasing age category, greater proportions of Americans take vitamin/mineral supplements.
Using the Complex Samples Frequencies procedure, you have obtained statistics for the use of nutritional supplements among U.S. citizens. Overall, more Americans take vitamin/mineral supplements than not. When broken down by age category, greater proportions of Americans take vitamin/mineral supplements with increasing age.
The Complex Samples Frequencies procedure is a useful tool for obtaining univariate descriptive statistics of categorical variables for observations obtained via a complex sampling design. The Complex Samples Sampling Wizard is used to specify complex sampling design specifications and obtain a sample. The sampling plan file created by the Sampling Wizard contains a default analysis plan and can be specified in the Plan dialog box when you are analyzing the sample obtained according to that plan. The Complex Samples Analysis Preparation Wizard is used to set analysis specifications for an existing complex sample. The analysis plan file created by the Sampling Wizard can be specified in the Plan dialog box when you are analyzing the sample corresponding to that plan. The Complex Samples Crosstabs procedure provides descriptive statistics for the crosstabulation of categorical variables. The Complex Samples Descriptives procedure provides univariate descriptive statistics for scale variables.

158 Chapter 15

The Complex Samples Crosstabs procedure is a useful tool for obtaining descriptive statistics of the crosstabulation of categorical variables for observations obtained via a complex sampling design. The Complex Samples Sampling Wizard is used to specify complex sampling design specifications and obtain a sample. The sampling plan file created by the Sampling Wizard contains a default analysis plan and can be specified in the Plan dialog box when analyzing the sample obtained according to that plan. The Complex Samples Analysis Preparation Wizard is used to specify analysis specifications for an existing complex sample. The analysis plan file created by the Sampling Wizard can be specified in the Plan dialog box when analyzing the sample corresponding to that plan. The Complex Samples Frequencies procedure provides univariate descriptive statistics for categorical variables.
Using Complex Samples Ratios to Aid Property Value Assessment
A state agency is charged with ensuring that property taxes are fairly assessed from county to county. Taxes are based on the appraised value of the property, so the agency wants to track property values across counties to be sure that each countys records are equally up-to-date. Since resources for obtaining current appraisals are limited, the agency chose to employ complex sampling methodology to select properties. The sample of properties selected and their current appraisal information is collected in property_assess_cs_sample.sav, found in the \tutorial\sample_files\ subdirectory of the directory in which you installed SPSS. Use Complex Samples Ratios to assess the change in property values since the last appraisal across the five counties.
E To run a Complex Samples Ratios analysis, from the menus choose: Analyze Complex Samples Ratios.
160 Chapter 16 Figure 16-1 Complex Samples Plan dialog box
installed SPSS and select property_assess.csplan.
161 Complex Samples Ratios Figure 16-2 Complex Samples Ratios dialog box
E Select Current value as a numerator variable. E Select Value at last appraisal as the denominator variable. E Select County as a subpopulation variable. E Click Statistics.
162 Chapter 16 Figure 16-3 Ratios Statistics dialog box
E Select Confidence interval, Unweighted count, and Population size in the Statistics group. E Select t-test and enter 1.3 as the test value. E Click Continue. E Click OK in the Complex Samples Ratios dialog box.

Ratios

Figure 16-4 Ratios table
The default display of the table is very wide, so you will need to pivot it for a better view.
163 Complex Samples Ratios
Pivoting the Ratios Table
E Double-click the table to activate it. E From the Viewer menus choose: Pivot Pivoting Trays E Drag Numerator and then Denominator from the row to the layer. E Drag County from the row to the column. E Drag Statistics from the column to the row. E Close the pivoting trays window.

Pivoted Ratios Table

Figure 16-5 Pivoted ratios table
The ratios table is now pivoted so that statistics are easier to compare across counties.

164 Chapter 16

The ratio estimates range from a low of 1.195 in the Southern county to a high of 1.524 in the Western county. There is also quite a bit of variability in the standard errors, which range from a low of 0.029 in the Southern county to 0.068 in the Eastern county. Some of the confidence intervals do not overlap; thus, you can conclude that the ratios for the Western county are higher than the ratios for the Northern and Southern counties. Finally, as a more objective measure, note that the significance values for the t tests for the Western and Southern counties are less than 0.05. Thus, you can conclude that the ratio for the Western county is greater than 1.3 and the ratio for the Southern county is less than 1.3.
Using the Complex Samples Ratios procedure, you have obtained various statistics for the ratios of Current value to Value at last appraisal. The results suggest that there may be certain inequities in the assessment of property taxes from county to county, namely: The ratios for the Western county are high, indicating that their records are not as up-to-date as other counties with respect to the appreciation of property values. Property taxes are probably too low in this county. The ratios for the Southern county are low, indicating that their records are more up-to-date than the other counties with respect to the appreciation of property values. Property taxes are probably too high in this county. The ratios for the Southern county are lower than those of the Western county but are still within the objective goal of 1.3. Resources used to track property values in the Southern county will be reassigned to the Western county to bring these counties ratios in line with the others and with the goal of 1.3.

165 Complex Samples Ratios
The Complex Samples Ratios procedure is a useful tool for obtaining univariate descriptive statistics of the ratio of scale measures for observations obtained via a complex sampling design. The Complex Samples Sampling Wizard is used to specify complex sampling design specifications and obtain a sample. The sampling plan file created by the Sampling Wizard contains a default analysis plan and can be specified in the Plan dialog box when you are analyzing the sample obtained according to that plan. The Complex Samples Analysis Preparation Wizard is used to specify analysis specifications for an existing complex sample. The analysis plan file created by the Sampling Wizard can be specified in the Plan dialog box when you are analyzing the sample corresponding to that plan. The Complex Samples Descriptives procedure provides descriptive statistics for individual scale measures.
Using Complex Samples General Linear Model to Fit a Two-Factor ANOVA
A grocery store chain surveyed a set of customers concerning their purchasing habits, according to a complex design. Given the survey results and how much each customer spent in the previous month, the store wants to see if the frequency with which customers shop is related to the amount they spend in a month, controlling for the gender of the customer and incorporating the sampling design. This information is collected in grocery_1month_sample.sav, found in the \tutorial\sample_files\ subdirectory of the directory in which you installed SPSS. Use the Complex Samples General Linear Model procedure to perform a two-factor (or two-way) ANOVA on the amounts spent.
E To run a Complex Samples General Linear Model analysis, from the menus choose: Analyze Complex Samples General Linear Model.
168 Chapter 17 Figure 17-1 Complex Samples Plan dialog box
installed SPSS and select grocery.csplan.
169 Complex Samples General Linear Model Figure 17-2 General Linear Model dialog box
E Select Amount spent as the dependent variable. E Select Who shopping for and Use coupons as factors. E Click Model.
170 Chapter 17 Figure 17-3 Model dialog box
E Choose to build a Custom model. E Select Main effects as the type of term to build and select shopfor and usecoup

as model terms.

E Select Interaction as the type of term to build and add the shopfor*usecoup interaction

as a model term.

E Click Continue. E Click Statistics in the General Linear Model dialog box.
171 Complex Samples General Linear Model Figure 17-4 General Linear Model Statistics dialog box
E Select Estimate, Standard error, Confidence interval, and Design effect in the Model

Parameters group.

E Click Continue. E Click Estimated Means in the General Linear Model dialog box.
172 Chapter 17 Figure 17-5 General Linear Model Estimated Means dialog box

191 Complex Samples Logistic Regression Figure 18-11 Odds ratios for years with current employer
This table displays the odds ratio of Previously defaulted for a unit change in the covariate Years with current employer. The reported value is the ratio of the odds of default for a person with 7.99 years at their current job compared to the odds of default for a person with 6.99 years (the mean).
Figure 18-12 Odds ratios for debt to income ratio
This table displays the odds ratio of Previously defaulted for a unit change in the covariate Debt to income ratio. The reported value is the ratio of the odds of default for a person with a debt/income ratio of 10.9341 compared to the odds of default for a person with 9.9341 (the mean). Note that because none of these predictors are part of interaction terms, the values of the odds ratios reported in these tables are equal to the values of the exponentiated parameter estimates. When a predictor is part of an interaction term, its odds ratio as reported in these tables will also depend on the values of the other predictors that make up the interaction.

192 Chapter 18

Using the Complex Samples Logistic Regression Procedure, you have constructed a model for predicting the probability that a given customer will default on a loan. A critical issue for loan officers is the cost of Type I and Type II errors. That is, what is the cost of classifying a defaulter as a non-defaulter (Type I)? What is the cost of classifying a non-defaulter as a defaulter (Type II)? If bad debt is the primary concern, then you want to lower your Type I error and maximize your sensitivity. If growing your customer base is the priority, then you want to lower your Type II error and maximize your specificity. Usually, both are major concerns, so you have to choose a decision rule for classifying customers that gives the best mix of sensitivity and specificity.
The Complex Samples Logistic Regression procedure is a useful tool for modeling a categorical variable when the cases have been drawn according to a complex sampling scheme. The Complex Samples Sampling Wizard is used to specify complex sampling design specifications and obtain a sample. The sampling plan file created by the Sampling Wizard contains a default analysis plan and can be specified in the Plan dialog box when you are analyzing the sample obtained according to that plan. The Complex Samples Analysis Preparation Wizard is used to specify analysis specifications for an existing complex sample. The analysis plan file created by the Sampling Wizard can be specified in the Plan dialog box when you are analyzing the sample corresponding to that plan. The Complex Samples General Linear Model procedure allows you to model a scale response.