Statistické metody pro analýzu dat s chybějícími pozorováními

Statistické metody pro analýzu dat s chybějícími pozorováními

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Mechanisms of missing data and methods are described in this thesis. Three mechanisms are considered - MCAR, MAR, MNAR. Two simple methods using deletion of incomplete records are shown and their properties and shortcomings are demonstrated. Secondly, the principle of simple imputations is explained...

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Bibliographic Details
Main Author: Janoušková, Kateřina
Other Authors: Omelka, Marek
Format: Dissertation
Language:Czech
Published: 2016
Online Access:http://www.nusl.cz/ntk/nusl-352770
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spelling ndltd-nusl.cz-oai-invenio.nusl.cz-3527702017-09-20T04:20:24Z Statistické metody pro analýzu dat s chybějícími pozorováními Statistical analysis of datasets with missing observations Janoušková, Kateřina Omelka, Marek Kulich, Michal Mechanisms of missing data and methods are described in this thesis. Three mechanisms are considered - MCAR, MAR, MNAR. Two simple methods using deletion of incomplete records are shown and their properties and shortcomings are demonstrated. Secondly, the principle of simple imputations is explained. EM algorithm which uses the classical statistics and the algorithm of data augmentation which uses Bayesian framework are derived and compared. The last method included in the thesis is the multiple imputation. The described methods are compared on real data set, first on continuous variables and then on a contingency table. 1 2016 info:eu-repo/semantics/masterThesis http://www.nusl.cz/ntk/nusl-352770 cze info:eu-repo/semantics/restrictedAccess
collection NDLTD
language Czech
format Dissertation
sources NDLTD
description Mechanisms of missing data and methods are described in this thesis. Three mechanisms are considered - MCAR, MAR, MNAR. Two simple methods using deletion of incomplete records are shown and their properties and shortcomings are demonstrated. Secondly, the principle of simple imputations is explained. EM algorithm which uses the classical statistics and the algorithm of data augmentation which uses Bayesian framework are derived and compared. The last method included in the thesis is the multiple imputation. The described methods are compared on real data set, first on continuous variables and then on a contingency table. 1
author2 Omelka, Marek
author_facet Omelka, Marek
Janoušková, Kateřina
author Janoušková, Kateřina
spellingShingle Janoušková, Kateřina
Statistické metody pro analýzu dat s chybějícími pozorováními
author_sort Janoušková, Kateřina
title Statistické metody pro analýzu dat s chybějícími pozorováními
title_short Statistické metody pro analýzu dat s chybějícími pozorováními
title_full Statistické metody pro analýzu dat s chybějícími pozorováními
title_fullStr Statistické metody pro analýzu dat s chybějícími pozorováními
title_full_unstemmed Statistické metody pro analýzu dat s chybějícími pozorováními
title_sort statistické metody pro analýzu dat s chybějícími pozorováními
publishDate 2016
url http://www.nusl.cz/ntk/nusl-352770
work_keys_str_mv AT janouskovakaterina statistickemetodyproanalyzudatschybejicimipozorovanimi
AT janouskovakaterina statisticalanalysisofdatasetswithmissingobservations
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