From among the remaining raions (containing more than 95.5 percent of the population), three very large population units were selected with certainty: Moscow city, Moscow Oblast, and St. As in many national surveys involving face-to-face interviews, some remote areas were eliminated to contain costs also, Chechnya was eliminated because of armed conflict.
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These were allocated into 38 strata, based largely on geographical factors and level of urbanization, but were also based on ethnicity where there was salient variability. First, a list of 2,029 consolidated raions (similar to counties) was created from which to draw primary sample units (PSUs). A multistage probability sample was employed to draw the sample of dwelling units. A more detailed discussion of the issues is available here. No other sub-national portions of the sample are representative of their geographic or administrative areas. At the sub-national level, the Moscow and St. The RLMS sample is representative of the Russian Federation at the national-level. Sample Design and Methods Is the sample representative? Access to the text data requires stricter IRB review than does access to most of the data. Moreover, these responses are in Russian. Therefore, the text data are not distributed with the remaining variables. Since these responses are unique to the respondent, the likelihood of disclosing the respondent’s identity is high. These questions can be identified in the questionnaire by the note “(char)” under the variable name to the left of the question. Many responses to questions were recorded verbatim and were not coded into categories. These questions were added at the request of a funding agency in Russia and are not for public distribution. Why are some questions in the questionnaire but not in the data file? Since “not applicable” and “legitimate missing” are equivalent, some files use the “.” missing value for both meanings (that is, you will not find “.A” in those files). First confirm that the variables you are converting do not contain any legitimate negative values in the range -6 to -9 before making these changes and edit the code as needed.
SPSS CODE NOT APPLICALBE AS MISSING SOFTWARE
Those who are converting the data to a software product that does not provide multiple missing value codes, and who want to preserve these distinctions, may use the following code in SAS to convert the missing values to numeric values. = legitimate missing (due to skip instruction)
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The RLMS data take advantage of this feature to code missing values as follows: , that are all treated as missing by statistical procedures. Data Variables and Codes What do the missing values codes.