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Estimation of Measurement Error Using Local Sampling and Joint Nonparametric Linearisation

100%
Górkiewicz M., University J.
Acta Universitatis Lodziensis. Folia Oeconomica
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2002
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vol. 162
EN
This paper presents how to use the near neighbours technique in aim to transform a given data set (Z, X, YT) of size N into a set of J ~ N local samples (Z, X), with restrictions on minimal number К of members in each local sample and on maximal difference of Y inside each local sample, where Z plays role of an outcome, X is an independent variable, and Y1 - (Y ..., YL) is a vector of L supplementary continuous variables. Then the procedure for non-parametric joint linearisation of an obtained set of local samples was proposed. The whole proposed method was applied to estimation of models with standard deviation of measurements as outcome Z and measured value as independent variable X. The paper was inspired by difficulties with estimation of the measurement error, which often occur in medicine, if accuracy of a measurement procedure depends on some properties of patient. Nevertheless, the proposed approach seems to be more general. It can be useful in many analyses of observational studies, which aim to estimate a family of the functions, preferable the linear ones, instead a single multivariate model.
PL
Praca prezentuje zastosowanie techniki najbliższych sąsiadów w celu przekształcenia zbioru N danych postaci (Z, X, YT) w zbiór J ~ N prób lokalnych (Z, X), przy ograniczeniach dotyczących minimalnej liczby danych К oraz różnic wartości YT w każdej próbie lokalnej, gdzie Z pełni rolę zmiennej zależnej, X - zmiennej niezależnej, a Y1 = (Y, ..., YL) jest L-wymiarową zmienną dodatkową. Następnie proponuje się procedurę nieparametrycznej łącznej linearyzacji zbioru prób lokalnych. Obie procedury proponuje się stosować do oceny dokładności metod pomiarowych, z odchyleniem standardowym błędu pomiarów jako zmienną Z i wielkością mierzoną jako zmienną X. Proponowane podejście może być użyteczne w innych zastosowaniach, kiedy zamiast modelu regresji wielowymiarowej estymuje się rodzinę zależności regresyjnych.
2
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Small Area Prediction under Alternative Model Specifications

88%
Erciulescu A. L., Fuller W. A.
Statistics in Transition new series
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2016
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vol. 17
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issue 1
9-24
EN
Construction of small area predictors and estimation of the prediction mean squared error, given different types of auxiliary information are illustrated for a unit level model. Of interest are situations where the mean and variance of an auxiliary variable are subject to estimation error. Fixed and random specifications for the auxiliary variables are considered. The efficiency gains associated with the random specification for the auxiliary variable measured with error are demonstrated. A parametric bootstrap procedure is proposed for the mean squared error of the predictor based on a logit model. The proposed bootstrap procedure has smaller bootstrap error than a classical double bootstrap procedure with the same number of samples.
3
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Efficient estimation of population mean in the presence of non-response and measurement error

88%
Tiwari K. K., Sharma V.
Statistics in Transition new series
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2023
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vol. 24
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issue 3
95-116
EN
In real-world surveys, non-response and measurement errors are common, therefore studying them together seems rational. Some population mean estimators are modified and studied in the presence of non-response and measurement errors. Bias and mean squared error expressions are derived under different cases. For all estimators, a theoretical comparison is made with the sample mean per unit estimator. The Monte-Carlo simulation is used to present a detailed picture of all estimators' performance.
4
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The selection of Survey Modes on the Basis of Respondents' Preference Analysis

75%
Rybak A.
ASK. Research and Methods
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2018
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vol. 27
23-40
EN
The following study addresses the problem of predicting the respondents’ survey preferences when implementing a mixed-mode survey design. Most previous experimental research implies that offering respondents the choice of modes results in a drop in response rates. The consequence of that effect is a need to establish survey mode preference predictors that will make the improvement of mixed-mode survey quality possible. Sending a request for participation in the applied mode to a subcategory of the sample, the one we suppose would most likely prefer that mode, can raise response rates, and quality of measurement, and sometimes reduce the costs of the research. Because of the practical aspect, these predictors should be included or be deducible from the survey frame and restricted to the specific socio-cultural area. This article will include an overview both of strategies of mode preference research and of possible predictors of preference itself. Then the ESS Mixed Mode Experiment from 2015 conducted by the team from the Polish Academy of Sciences will be presented. The data from this experiment was used to create logistic regression models analyzing which socio-demographic variables influence the mode preference among Polish respondents. One possible application is use of the conclusions to address future participation requests, which will be based on the mode probably preferred by the specific sample members.
5
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Pomiar statusu osób na rynku pracy w Narodowym Spisie Powszechnym Ludności i Mieszkań 2011

63%
Lańduch P.
Wiadomości Statystyczne. The Polish Statistician
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2017
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issue 2
98-111
PL
Wielokrotny pomiar statusu osób na rynku pracy z wykorzystaniem kwestionariusza statystycznego może posłużyć do zastosowania metod ilościowych do oceny jego jakości. W celu oceny jakości wyników badania stosuje się m.in. metody powtórnego, a także wielokrotnego pomiaru na wybranej próbie losowej. Na podstawie danych uzyskanych z Narodowego Spisu Powszechnego Ludności i Mieszkań przeprowadzonego w 2011 r. (NSP 2011), zaprezentowano zastosowanie współczynnika zgodności Cohena oraz analizy klasy ukrytej do oceny jakości klasyfikowania osoby na rynku pracy. Pytania kwestionariusza spisowego pozwoliły na ocenę statusu osób na rynku pracy zgodnie z rekomendacją Międzynarodowej Organizacji Pracy (MOP) i samooceny respondenta. W artykule przedstawiono tylko kwestię zgodności wyników uzyskanych w tych ujęciach w części spisu opartej na próbie losowej, pomijając wiele innych zagadnień dotyczących błędów losowych i nielosowych.
EN
Multimeasurement of the person’s labour market status based on the statistical questionnaire may be used for the assessment of its quality with quantitative methods. In order to evaluate the measurement quality we employ among others, remeasurement or multiple measurements for a random sample of units. Based on the data from the National Population and Housing Census 2011, this article presents appliance of the Cohen’s coefficient of contingency and Latent Class Analysis for the assessment of respondent’s labour force classification. The questions in the census questionnaire enable the evaluation of persons’ labour market status according to International Labour Organisation (ILO) recommendation as well as give an opportunity to respondent’s self-assessment. The article focuses on the issue of results’ consistency obtained from these two types of information in the part of the Census based on a random sample. Many other aspects relating to random and non-random errors were omitted in the research.
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