Conventional data analysis concentrates on individual surveys of not more than 2000 respondents. Hypotheses regarding small sub-groups of the population cannot be tested with these surveys. Special surveys with disproportionate samples or with a sample size of over 2.000 respondents are expensive. The cumulation of surveys for the use of secondary analyses can be regarded as a first step towards the solution of this problem. The following problems of the cumulation of surveys are discussed in this paper: 1. Technical problems concerning conditions which single surveys have to fulfil for cumulation, and questions of computer equipment to handle a large amount of data; 2. cost problems; 3. sampling problems, e.a. estimates of single surveys in comparison with estimates of a cumulated survey; 4. problems of equivalence of indicators. Finally other possibilities of analyses with cumulated surveys are discussed.
Conventional data analysis concentrates on individual surveys of not more than 2000 respondents. Hypotheses regarding small sub-groups of the population cannot be tested with these surveys. Special surveys with disproportionate samples or with a sample size of over 2.000 respondents are expensive. The cumulation of surveys for the use of secondary analyses can be regarded as a first step towards the solution of this problem. The following problems of the cumulation of surveys are discussed in this paper: 1. Technical problems concerning conditions which single surveys have to fulfil for cumulation, and questions of computer equipment to handle a large amount of data; 2. cost problems; 3. sampling problems, e.a. estimates of single surveys in comparison with estimates of a cumulated survey; 4. problems of equivalence of indicators. Finally other possibilities of analyses with cumulated surveys are discussed.