Techn. Universiẗat, Diss., 2004--Dresden.

Zugl.: Wuppertal, Univ., Diss., 2008

Zugl.: Wuppertal, Universiẗat, Diss., 2008.

Konstanz, Univ., Diplomarb., 2007.

No description available.

This diploma thesis shows a connection between an interviewer's demographic characteristics and a respondent's answers during a face-to-face interview. The analysis uses the American data from General Social Survey and the Czech data from CVVM. The monitored variables are sex, age, education and the size of place. On the ground of the theory of interpersonal communication, social distance and stereotypical answers to certain questions the following questions were chosen to be analysed: the willingness to have certain group of people as neighbours, opinions on marihuana, the death penalty, abortions and homosexuals. The analysis proves that the interviewer's demographic characteristics do influence the answers to some of these questions. However there is no set of rules that could prove which particular characteristics would influence which particular questions. The methods used in this thesis are correlational analysis, binary logistic regression and an advanced mixed models analysis. The next part consists of a qualitative research, which uses a fictional face-to-face interviews and following cognitive interviews with respondents. This part shows the importance of the actual question because when the respondent answers a certain question for the first time he is more likely to be influenced by the...

<p>This thesis focuses on measurement errors that could be ascribed to the interviewers. To study interviewer variability a measurement error model is formulated which makes a clear distinction between three sources of randomness: the sample selection, interviewer assignment, and interviewing. </p><p>In the first paper the variance of the observed sample mean is derived, and it is seen how this variance depends on parameters of the measurement error model and on the number of interviewers. An estimator of the interviewer variance, which is seen to be unbiased, and a biased intra-interviewer correlation estimator are suggested. In a simulation study it is seen that the simulation variance of the interviewer variance estimator increases for both high and low interviewer assignments and seems to have a minimum somewhere in between. </p><p>The second paper presents an expression of the variance of the observed sample mean under stratified random sampling. Two possible estimators of the variance of the mean are considered, one of which has a slight positive bias, the other a negative bias, which can be large. Two different estimators of the interviewer variance are studied. Only one of them makes it possible to find a reasonable estimate of the intra-interviewer correlation. </p><p>In the third paper an expression for the variance of the interviewer variance estimator is derived. This result may prove useful in designing future studies of interviewer variance. For a large population it will be possible to use an approximate variance, irrespective of the underlying distribution of the unknown true values.</p><p>The fourth paper deals with some issues in planning and analyzing an interviewer variance study. Three problems are considered: (i) Determining the number of interviewers and the appropriate size of the interviewer assignments; (ii) Finding the probability of negative estimates of the interviewer variance; (iii) Testing for interviewer variance.</p>

The thesis deals with the survey, specifically its quality and the associated total survey error. Particularly it is focused on those activities, which are linked with the activity of interviewer. Subsequently, this is related to interviewers of the Public Opinion Research Centre. The first part deals with the concept of total survey error. It summarizes the basic concepts and possible points of view on error and data quality. The work also deals with the complexity of the total error and of interdependence of its components. Today's new concepts of research quality are introduced. Briefly it is mentioned the history of surveys, of their methodology and quality. Another part is from the perspective of data quality focused on the interviewer's work and possible influences on the course of questioning, which are associated. The various activities with regard to possible sources of error are discussed. From this perspective, it is mapped and evaluated the activity of interviewers of CVVM and some improvement of work with interviewers is designed.

This thesis focuses on measurement errors that could be ascribed to the interviewers. To study interviewer variability a measurement error model is formulated which makes a clear distinction between three sources of randomness: the sample selection, interviewer assignment, and interviewing. In the first paper the variance of the observed sample mean is derived, and it is seen how this variance depends on parameters of the measurement error model and on the number of interviewers. An estimator of the interviewer variance, which is seen to be unbiased, and a biased intra-interviewer correlation estimator are suggested. In a simulation study it is seen that the simulation variance of the interviewer variance estimator increases for both high and low interviewer assignments and seems to have a minimum somewhere in between. The second paper presents an expression of the variance of the observed sample mean under stratified random sampling. Two possible estimators of the variance of the mean are considered, one of which has a slight positive bias, the other a negative bias, which can be large. Two different estimators of the interviewer variance are studied. Only one of them makes it possible to find a reasonable estimate of the intra-interviewer correlation. In the third paper an expression for the variance of the interviewer variance estimator is derived. This result may prove useful in designing future studies of interviewer variance. For a large population it will be possible to use an approximate variance, irrespective of the underlying distribution of the unknown true values. The fourth paper deals with some issues in planning and analyzing an interviewer variance study. Three problems are considered: (i) Determining the number of interviewers and the appropriate size of the interviewer assignments; (ii) Finding the probability of negative estimates of the interviewer variance; (iii) Testing for interviewer variance.

Measures of data quality are important for the evaluation and improvement of survey design and procedures. A detailed investigation of the sources, magnitude and impact of errors is necessary to identify how survey design and procedures may be improved and how resources allocated more efficiently among various aspects of the survey operation. A major part of this thesis is devoted to the overview of statistical theory and methods for measuring the contribution of response variability to the overall error of a survey. A very common practice in surveys is to select groups (clusters) of elements together instead of independent selection of elements. In practice cluster samples tend to produce higher sampling variance for statistics than element samples of the same size. Their frequent use stems from the desirable cost features that they have. Most data collection and sample designs involve some overlapping between interviewer workload and the sampling units (clusters). For those cases, a proportion of the measurement variance, which is due to interviewers, is reflected to some degree in the sampling variance calculations. The prime purpose in this thesis is to determine a variance formula that decomposes the total variance into sampling and measurement variance components for two commonly used data collection and sample designs. Once such a decomposition is obtained, determining an optimum allocation in existence of measurement errors would be possible.