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Paradata information can be used to help achieve the goals of a survey. For example, early responses may be mainly from one type of respondent, and the collectors knowing this can focus on reaching the other types so the survey has good coverage of the intended population. Thus survey efforts can be dynamically responsive to the paradata. [5]
A single survey is made of at least a sample (or full population in the case of a census), a method of data collection (e.g., a questionnaire) and individual questions or items that become data that can be analyzed statistically. A single survey may focus on different types of topics such as preferences (e.g., for a presidential candidate ...
Survey methodology is "the study of survey methods". [1] As a field of applied statistics concentrating on human-research surveys, survey methodology studies the sampling of individual units from a population and associated techniques of survey data collection, such as questionnaire construction and methods for improving the number and accuracy of responses to surveys.
A probability-based survey sample is created by constructing a list of the target population, called the sampling frame, a randomized process for selecting units from the sample frame, called a selection procedure, and a method of contacting selected units to enable them to complete the survey, called a data collection method or mode. [10]
In survey research, the design effect is a number that shows how well a sample of people may represent a larger group of people for a specific measure of interest (such as the mean). This is important when the sample comes from a sampling method that is different than just picking people using a simple random sample .
Sample size determination or estimation is the act of choosing the number of observations or replicates to include in a statistical sample.The sample size is an important feature of any empirical study in which the goal is to make inferences about a population from a sample.
Traditionally, much of the data gathered in DHS surveys is self-reported. Biomarkers complement this information by providing an objective profile of a specific disease or health condition in a population. Biomarker data contributes to the understanding of behavioral risk factors and determinants of different illnesses. [citation needed]
For example, an electronic survey method might influence results for those who might be unfamiliar with an electronic survey interface differently than for those who might be familiar. If measures are affected by CMV or common-method bias , the intercorrelations among them can be inflated or deflated depending upon several factors. [ 3 ]