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Total Survey Error
In survey sampling, total survey error includes all forms of survey error including sampling variability, interviewer effects, frame errors, response bias, and non-response bias. Total survey error is discussed in detail in many sources including Salant and Dillman. Definition Total survey error is the difference between a population parameter (such as the mean, total or proportion) and the estimate of that parameter based on the sample survey or census. It has two components: sampling error and nonsampling error. Sampling error, which occurs in sample surveys but not censuses results from the variability inherent in using a randomly selected fraction of the population for estimation. Nonsampling error, which occurs in surveys and censuses alike, is the sum of all other errors, including errors in frame construction, sample selection, data collection, data processing and estimation methods. Sources of nonsampling error The survey literature decomposes nonsampling errors into five ...
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Survey Sampling
In statistics, survey sampling describes the process of selecting a sample of elements from a target population to conduct a survey. The term "survey" may refer to many different types or techniques of observation. In survey sampling it most often involves a questionnaire used to measure the characteristics and/or attitudes of people. Different ways of contacting members of a sample once they have been selected is the subject of survey data collection. The purpose of sampling is to reduce the cost and/or the amount of work that it would take to survey the entire target population. A survey that measures the entire target population is called a census. A sample refers to a group or section of a population from which information is to be obtained Survey samples can be broadly divided into two types: probability samples and super samples. Probability-based samples implement a sampling plan with specified probabilities (perhaps adapted probabilities specified by an adaptive procedur ...
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Sampling Error
In statistics, sampling errors are incurred when the statistical characteristics of a population are estimated from a subset, or sample, of that population. Since the sample does not include all members of the population, statistics of the sample (often known as estimators), such as means and quartiles, generally differ from the statistics of the entire population (known as parameters). The difference between the sample statistic and population parameter is considered the sampling error.Sarndal, Swenson, and Wretman (1992), Model Assisted Survey Sampling, Springer-Verlag, For example, if one measures the height of a thousand individuals from a population of one million, the average height of the thousand is typically not the same as the average height of all one million people in the country. Since sampling is almost always done to estimate population parameters that are unknown, by definition exact measurement of the sampling errors will not be possible; however they can often be ...
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Interviewer Effect
The interviewer effect (also called interviewer variance or interviewer error) is the distortion of response to a personal or telephone interview which results from differential reactions to the social style and personality of interviewers or to their presentation of particular questions. The use of fixed-wording questions is one method of reducing interviewer bias. Anthropological research and case-studies are also affected by the problem, which is exacerbated by the self-fulfilling prophecy, when the researcher is also the interviewer it is also any effect on data gathered from interviewing people that is caused by the behavior or characteristics (real or perceived) of the interviewer. Interviewer effects can also be associated with the characteristics of the interviewer, such as race. Whether black respondents are interviewed by white interviewers or black interviewers has a strong impact on their responses to both attitude questions and behavioral ones. In the latter case, for ex ...
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Sampling Frame
In statistics, a sampling frame is the source material or device from which a sample is drawn. It is a list of all those within a population who can be sampled, and may include individuals, households or institutions. Importance of the sampling frame is stressed by Jessen and Salant and Dillman.Salant, Priscilla, and Don A. Dillman. "How to Conduct your own Survey: Leading professional give you proven techniques for getting reliable results" (1995) Obtaining and organizing a sampling frame In the most straightforward cases, such as when dealing with a batch of material from a production run, or using a census, it is possible to identify and measure every single item in the population and to include any one of them in our sample; this is known as ''direct element sampling''. However, in many other cases this is not possible; either because it is cost-prohibitive (reaching every citizen of a country) or impossible (reaching all humans alive). Having established the frame, there ar ...
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Response Bias
Response bias is a general term for a wide range of tendencies for participants to respond inaccurately or falsely to questions. These biases are prevalent in research involving participant self-report, such as structured interviews or surveys. Response biases can have a large impact on the validity of questionnaires or surveys. Response bias can be induced or caused by numerous factors, all relating to the idea that human subjects do not respond passively to stimuli, but rather actively integrate multiple sources of information to generate a response in a given situation. Because of this, almost any aspect of an experimental condition may potentially bias a respondent. Examples include the phrasing of questions in surveys, the demeanor of the researcher, the way the experiment is conducted, or the desires of the participant to be a good experimental subject and to provide socially desirable responses may affect the response in some way. All of these "artifacts" of survey and self ...
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Non-response Bias
Participation bias or non-response bias is a phenomenon in which the results of elections, Research, studies, Opinion poll, polls, etc. become non-representative because the participants disproportionately possess certain traits which affect the outcome. These traits mean the sample is systematically different from the target population, potentially resulting in biased estimates. For instance, a study found that those who refused to answer a survey on AIDS tended to be "older, attend church more often, are less likely to believe in the confidentiality of surveys, and have lower sexual self disclosure." It may occur due to several factors as outlined in W. Edwards Deming, Deming (1990). Non-response bias can be a problem in Longitudinal study, longitudinal research due to Attrition bias, attrition during the study. Example If one selects a sample of 1000 managers in a field and polls them about their workload, the managers with a high workload may not answer the survey because th ...
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Sampling Error
In statistics, sampling errors are incurred when the statistical characteristics of a population are estimated from a subset, or sample, of that population. Since the sample does not include all members of the population, statistics of the sample (often known as estimators), such as means and quartiles, generally differ from the statistics of the entire population (known as parameters). The difference between the sample statistic and population parameter is considered the sampling error.Sarndal, Swenson, and Wretman (1992), Model Assisted Survey Sampling, Springer-Verlag, For example, if one measures the height of a thousand individuals from a population of one million, the average height of the thousand is typically not the same as the average height of all one million people in the country. Since sampling is almost always done to estimate population parameters that are unknown, by definition exact measurement of the sampling errors will not be possible; however they can often be ...
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Nonsampling Error
In statistics, non-sampling error is a catch-all term for the deviations of estimates from their true values that are not a function of the sample chosen, including various systematic errors and random errors that are not due to sampling.Dodge, Y. (2003) ''The Oxford Dictionary of Statistical Terms'', OUP. Non-sampling errors are much harder to quantify than sampling errors.Fritz Scheuren (2005). "What is a Margin of Error?", Chapter 10, inWhat is a Survey?", American Statistical Association, Washington, D.C. Accessed 2008-01-08. Non-sampling errors in survey estimates can arise from: * Coverage errors, such as failure to accurately represent all population units in the sample, or the inability to obtain information about all sample cases; * Response errors by respondents due for example to definitional differences, misunderstandings, or deliberate misreporting; * Mistakes in recording the data or coding it to standard classifications; * Pseudo-opinions given by respondents wh ...
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Sampling Frame
In statistics, a sampling frame is the source material or device from which a sample is drawn. It is a list of all those within a population who can be sampled, and may include individuals, households or institutions. Importance of the sampling frame is stressed by Jessen and Salant and Dillman.Salant, Priscilla, and Don A. Dillman. "How to Conduct your own Survey: Leading professional give you proven techniques for getting reliable results" (1995) Obtaining and organizing a sampling frame In the most straightforward cases, such as when dealing with a batch of material from a production run, or using a census, it is possible to identify and measure every single item in the population and to include any one of them in our sample; this is known as ''direct element sampling''. However, in many other cases this is not possible; either because it is cost-prohibitive (reaching every citizen of a country) or impossible (reaching all humans alive). Having established the frame, there ar ...
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Statistical Model Specification
In statistics, model specification is part of the process of building a statistical model: specification consists of selecting an appropriate functional form for the model and choosing which variables to include. For example, given personal income y together with years of schooling s and on-the-job experience x, we might specify a functional relationship y = f(s,x) as follows: : \ln y = \ln y_0 + \rho s + \beta_1 x + \beta_2 x^2 + \varepsilon where \varepsilon is the unexplained error term that is supposed to comprise independent and identically distributed Gaussian variables. The statistician Sir David Cox has said, "How hetranslation from subject-matter problem to statistical model is done is often the most critical part of an analysis". Specification error and bias Specification error occurs when the functional form or the choice of independent variables poorly represent relevant aspects of the true data-generating process. In particular, bias (the expected value of the di ...
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Measurement Error
Observational error (or measurement error) is the difference between a measured value of a quantity and its true value.Dodge, Y. (2003) ''The Oxford Dictionary of Statistical Terms'', OUP. In statistics, an error is not necessarily a " mistake". Variability is an inherent part of the results of measurements and of the measurement process. Measurement errors can be divided into two components: ''random'' and ''systematic''. Random errors are errors in measurement that lead to measurable values being inconsistent when repeated measurements of a constant attribute or quantity are taken. Systematic errors are errors that are not determined by chance but are introduced by repeatable processes inherent to the system. Systematic error may also refer to an error with a non-zero mean, the effect of which is not reduced when observations are averaged. Measurement errors can be summarized in terms of accuracy and precision. Measurement error should not be confused with measurement uncer ...
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Public Opinion Quarterly
''Public Opinion Quarterly'' is an academic journal published by Oxford University Press for the American Association for Public Opinion Research, covering communication studies and political science. It was established in 1937 and according to the ''Journal Citation Reports'', the journal has a 2015 impact factor of 1.429, ranking it 20th out of 79 journals in the category "Communication", 37th out of 163 journals in the category "Political Science" and 18th out of 93 journals in the category "Social Sciences, Interdisciplinary". The journal was originally sponsored by Princeton University's Woodrow Wilson School of Public and International Affairs. Its first editor-in-chief was former diplomat DeWitt Clinton Poole. See also * List of political science journals This is a list of political science journals presenting representative academic journals in the field of political science. A *''Acta Politica'' *''African Affairs'' *''American Journal of Political Science'' *''Ame ...
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