Geographic Entities Over Time
Just as there are issues of comparability regarding specific data items (white population in 1990 is not the same in 2000; Median Household Income needs to be put in comparable inflation-adjusted dollars, etc.) there are also issues related to the geographic area(s) being summarized. While it is straightforward for most larger areas (the U.S., states and most counties), it can be very problematic for some levels of geography. For example, ZIP codes are infamous for changing their spatial definitions. The area comprising ZIP 63303 in 1990 may well be quite different from the 2000 version. It is important to know what, if anything, may have been done to "adjust" the geographies to make them comparable over time. It varies with the kind of geographic entity.
Here is how we handle the different types:
- Political entities (states, counties, places): These are reported using the definitions as of the census. If a city has doubled in size over the decade via annexation, the 1990 data will not be a summary of the current city limits, but rather the city as it was defined at the time of the 1990 census (January 1, 1990 to be more precise.)
- ZIP codes: These are again based on the definitions used at the time of each census. For 1990 we use the data as published on Summary Tape File 3B. You need to be extremely careful when drawing conclusions about a trend within a ZIP code because it is very possible that the geographic entity summarized in 1990 is not the same as the one summarized in 2000. A good way to see if this is a problem is to look at the changes in Total Population and Persons Per Square Mile in Table 1. If the land area did not change over the decade then the Percent Change in these two items should be the same. But if population went up 20% and persons per square mile only went up 5%, then you know that land area must have also gone up, and hence the geographic areas are not the same for the two decades. Note: land area in square miles is not explicitly shown in the reports, but it is a variable on the extract datasets (LandSQMI), and it can be derived by dividing the total population by the persons per square mile.
- Census Tracts and Block Groups: We only do trends at these levels within Missouri. The 1990 data used in these reports has been retabulated to estimate data values corresponding to the 2000 census codes. Thus you get trend data for census tracts that did not exist in 1990. You will notice that when you extract the 1990 data for these reports that the datasets accessed will have a name ending with "00", such as "motrs00.sas7bdat". This is an indication of a set that has been retabulated (the term "normalized" is sometimes used to describe this kind of restructuring) to 2000 geographic codes.
- School Districts and State Legislative Districts: Only available for Missouri. The school district data has been retabulated to the 2000 district definitions. Likewise, the state legistlative district data has been retabulated to the current (i.e. as redrawn for 2002) legislative districts.
- Metro Areas: These are as the time of each census. So the areas will not always correspond to the same geography.
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Printing the Tables
These tables area readily printable in portrait mode for most setups. It takes 7 pages to display the report using IE default settings. In IE (but not in Netscape at the moment) the column headers will repeat on each printed page. The name of the area being summarized is included in the html document title, which will normally print at the top of each page.
Downloading the Data
At the bottom of the report you will see a row of hyerlinks to important related pages. The second of these is "Extract Data via Uexplore/xtract". This refers to the MCDC's Uexplore web application for accessing our data collection. There are separate links for the 1990 and 2000 data. These links bypass the usual explore-the-directory phase of accessing a dataset, and take you directly to the xtract (data extraction utility application) first screen with the appropriate dataset already selected. The page includes a link to the online tutorial for the uexplore application (you may have to scroll to see the link -- located just below the line
First time users ....
You may need to specify a filter to avoid getting data for the entire dataset (this would typically involve coding a filter based on SumLev and/or State variables.) You will also have the opportunity to select variables so you do not have to take the entire 400 or so variables (it varies slightly with geographic level and year).
In fact, if you are using a csv file to load into Excel, you must limit the extraction to 256 variables or less. There is also a 65,xxx row limit in Excel, so you may have to code filters and break the data into subsets.
Displaying Specific Tables
Used mostly be the developers as a handy testing option, the dp3_2kt application supports a tables parameter. It allows telling the program which specific tables you want to have displayed. For example, specifying the URL with parms
?_PROGRAM=websas.dp3_2kt.sas&_SERVICE=sasapp&st=17&co=001&tables=7+8+9
would result in a display of just tables 7, 8 and 9 for Adams county, Illinois. If the parms is not specified then the default is to print all 29 of them.
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Linking to the Tables
The Missouri Census Data Center welcomes other State Data Centers to create web pages that point to these reports by coding URLs that point to the reports. These are of the form:
http://mcdc2.missouri.edu/cgi-bin/broker?_PROGRAM=websas.dp3_2kt.sas&_SERVICE=sasapp[PARMS}
where [PARMS} specifies what geographic entity is to be displayed. This is done using a series of mostly-2-character geographic parameter names and their values. Best way to see how it works is to use scan the menus and see the underlying URLs. Here are some typical examples:
) for a data item will take you to the location within the footnotes document pertaining to that item.