March 15, 2002 |
Analyzing TEDS Online |
In Brief |
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The Treatment Episode Data Set (TEDS) is
a compilation of data on the demographic characteristics and substance abuse
problems of those admitted for substance abuse treatment. The information
comes primarily from facilities that receive some public funding. Information
on treatment admissions are routinely collected by State administrative
systems and then submitted to SAMHSA in a standard format. Approximately
1.6 million records are included in TEDS each year.
The 1992 to 1999 TEDS files are available through the Substance Abuse and Mental Health Data Archive (SAMHDA) and the archive's online data analysis system (DAS).1,2 In this report, we will demonstrate the DAS recode and compute procedures and the comparison of means function. For a more basic overview of the DAS, click here to see the report, "Accessing and Analyzing the NHSDA Online," or go to: The recode and compute procedures allow users to temporarily store recoded or created variables on SAMHDA's web site. This is useful when you are running analyses over the course of several days or weeks. New variables are kept on the web site for 30 days after their last use. 3,4 Newly created variables are specific to the file for which they were created. For analyses across multiple years of a study, you must create the new variable for each year or file. Both the recode and the compute procedures present the user with screens on which to enter the specifications for creating a new variable. The user enters the input variable name(s), the rules to convert one or more existing variables into a new variable, labels for the new variable(s), and other specifications. The recode or compute application then reads these specifications and carries out the data transformations. Given the detailed geographic coding in TEDS, comparisons between geographic areas among several states or within the same state are possible. In doing these comparisons, it may be useful to create new variables. To illustrate, we will examine the variation of prior treatment episodes between Hispanics and non-Hispanics in New York State compared to the rest of the U.S. We will accomplish this in three steps using: (1) the recode procedure to collapse the existing ethnicity variable into two categories: Hispanic and Non-Hispanic; (2) the compute procedure to create another new variable with two categories, one for New York and one for all other states; and (3) the comparison of means function to determine the average number of prior treatments based on the two new variables. Access the DAS as follows:
Step 1
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Step 2 The compute procedure is designed primarily for manipulating variables mathematically. For example, you would use the compute procedure to create a new variable that is the sum of a set of existing variables by entering an algebraic expression to define the new variable. You may also use if-then-else logic to collapse variables into a smaller number of categories, as with the recode procedure. This example illustrates that capability. The original variable for state (named STATE) includes 52 codes, one for each state, plus the District of Columbia and Puerto Rico. Again, -9 indicates that data are missing. In Step 2, compute a new variable called NYSTATE that includes two codes, one for New York and one for all other states: From SDA Menu: Select Compute New Variable. Expression to Define New Variable: Enter the command syntax directly into theExpression box. Refer to the Help links for syntax examples such as using ge for greater than or equal to. Options: Click on your preferences for replacing an existing variable and handling missing data codes. Category Labels: Specify the new labels for each code. Start Computing: Click on this button to begin the computations. Figure 4 shows an excerpt from the compute input screen and Figure 5 shows the new codes and frequencies. |
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Step 3
From SDA Menu: Select Comparison of Means. Dependent Variable: Enter the variable name for number of prior treatment episodes, which is NOPRIOR. Row/Column Variables: Enter HISP as the row variable and NYSTATE as the column variable. Main Statistic: Accept the default of Means. Other Options: Choose your preferences for other options; we have chosen color-coding and the T-statistic. Optional statistics such as analysis of variance and confidence intervals also may be selected. Figure 6 shows an excerpt of the input screen.
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This page was last updated on December 31, 2008. |