{"id":{"repo_id":"cape-town","oai_identifier":"oai:open.uct.ac.za:11427/21912"},"canonical_url":"https://search.dev.ndltd.org/etd/cape-town/oai:open.uct.ac.za:11427/21912","repository":{"repo_id":"cape-town","name":"University of Cape Town","base_url":"https://open.uct.ac.za/oai/request"},"display":{"title":"The use of correspondence analysis in building loglinear models","abstract":"Data collected in the biomedical and social sciences by means of questionnaires is in most instances qualitative in nature. Such data, typically set out in the form of (multi-dimensional) contingency tables, is usually subjected to hypothesis testing in order to assess the interrelationships between the questions. Prior to undertaking confirmatory procedures, we argue that exploratory techniques should be used to gain a \"feel\" for the data. Correspondence Analysis (an exploratory data analysis procedure) and Log-linear Model building (a confirmatory data analysis procedure) are discussed before an investigation is undertaken to ascertain whether they can be used in conjunction. We found that correspondence analysis : (i) detects questions that are \"strictly\" independent/unrelated, (ii) detects pairwise relationships between questions (2-factor interactions) and thus can be used to suggest a splitting of large data sets into two or more subsets of questions that are independent, each of which can be analysed separately, and (iii) cannot be used to select log-linear models in general because it does not detect higher order interactions.","abstract_html":"Data collected in the biomedical and social sciences by means of questionnaires is in most instances qualitative in nature. Such data, typically set out in the form of (multi-dimensional) contingency tables, is usually subjected to hypothesis testing in order to assess the interrelationships between the questions. Prior to undertaking confirmatory procedures, we argue that exploratory techniques should be used to gain a "feel" for the data. Correspondence Analysis (an exploratory data analysis procedure) and Log-linear Model building (a confirmatory data analysis procedure) are discussed before an investigation is undertaken to ascertain whether they can be used in conjunction. We found that correspondence analysis : (i) detects questions that are "strictly" independent/unrelated, (ii) detects pairwise relationships between questions (2-factor interactions) and thus can be used to suggest a splitting of large data sets into two or more subsets of questions that are independent, each of which can be analysed separately, and (iii) cannot be used to select log-linear models in general because it does not detect higher order interactions.","abstract_has_math":false,"creators":["Parry, Charles David Heber"],"institution":"Department of Statistical Sciences","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Juritz, June"],"committee_chairs":[],"committee_members":[],"year":1983,"date_issued":"1983","date_published":"1983","updated_at":"2026-07-22T22:23:31Z","subjects":[],"languages":["eng"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/11427/21912","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Juritz, June"]},{"key":"dc:creator","label":"Author","values":["Parry, Charles David Heber"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2016-09-25T16:47:50Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2016-09-25T16:47:50Z"]},{"key":"dc:date.issued","label":"Date","values":["1983"]},{"key":"dc:publisher.department","label":"Dc Publisher Department","values":["Department of Statistical Sciences"]},{"key":"dc:publisher.institution","label":"Dc Publisher Institution","values":["University of Cape Town"]},{"key":"dc:type","label":"Dc Type","values":["Master Thesis"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["Masters"]},{"key":"dc:type.qualificationname","label":"Dc Type Qualificationname","values":["MSc"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["eng"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/11427/21912"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Data collected in the biomedical and social sciences by means of questionnaires is in most instances qualitative in nature. Such data, typically set out in the form of (multi-dimensional) contingency tables, is usually subjected to hypothesis testing in order to assess the interrelationships between the questions. Prior to undertaking confirmatory procedures, we argue that exploratory techniques should be used to gain a \"feel\" for the data. Correspondence Analysis (an exploratory data analysis procedure) and Log-linear Model building (a confirmatory data analysis procedure) are discussed before an investigation is undertaken to ascertain whether they can be used in conjunction. We found that correspondence analysis : (i) detects questions that are \"strictly\" independent/unrelated, (ii) detects pairwise relationships between questions (2-factor interactions) and thus can be used to suggest a splitting of large data sets into two or more subsets of questions that are independent, each of which can be analysed separately, and (iii) cannot be used to select log-linear models in general because it does not detect higher order interactions."]},{"key":"dc:title","label":"Title","values":["The use of correspondence analysis in building loglinear models"]}]}],"canonical_facts":{"dc:contributor.advisor":["Juritz, June"],"dc:creator":["Parry, Charles David Heber"],"dc:date.accessioned":["2016-09-25T16:47:50Z"],"dc:date.available":["2016-09-25T16:47:50Z"],"dc:date.issued":["1983"],"dc:description.abstract":["Data collected in the biomedical and social sciences by means of questionnaires is in most instances qualitative in nature. Such data, typically set out in the form of (multi-dimensional) contingency tables, is usually subjected to hypothesis testing in order to assess the interrelationships between the questions. Prior to undertaking confirmatory procedures, we argue that exploratory techniques should be used to gain a \"feel\" for the data. Correspondence Analysis (an exploratory data analysis procedure) and Log-linear Model building (a confirmatory data analysis procedure) are discussed before an investigation is undertaken to ascertain whether they can be used in conjunction. We found that correspondence analysis : (i) detects questions that are \"strictly\" independent/unrelated, (ii) detects pairwise relationships between questions (2-factor interactions) and thus can be used to suggest a splitting of large data sets into two or more subsets of questions that are independent, each of which can be analysed separately, and (iii) cannot be used to select log-linear models in general because it does not detect higher order interactions."],"dc:identifier.uri":["http://hdl.handle.net/11427/21912"],"dc:language.iso":["eng"],"dc:publisher.department":["Department of Statistical Sciences"],"dc:publisher.institution":["University of Cape Town"],"dc:title":["The use of correspondence analysis in building loglinear models"],"dc:type":["Master Thesis"],"dc:type.qualificationlevel":["Masters"],"dc:type.qualificationname":["MSc"]},"updated_at":"2026-07-22T22:23:31Z"}