Item tree analysis (ITA) is a data analytical method which allows constructing ahierarchical structure on the items of a questionnaire or test from observed responsepatterns. Assume that we have a questionnaire with m items and that subjects cananswer positive (1) or negative (0) to each of these items, i.e. the items aredichotomous. If n subjects answer the items this results in a binary data matrix Dwith m columns and n rows.Typical examples of this data format are test items which can be solved (1) or failed(0) by subjects. Other typical examples are questionnaires where the items arestatements to which subjects can agree (1) or disagree (0).Depending on the content of the items it is possible that the response of a subject to anitem j determines her or his responses to other items. It
Attributes | Values |
---|
rdfs:label
| |
rdfs:comment
| - Item tree analysis (ITA) is a data analytical method which allows constructing ahierarchical structure on the items of a questionnaire or test from observed responsepatterns. Assume that we have a questionnaire with m items and that subjects cananswer positive (1) or negative (0) to each of these items, i.e. the items aredichotomous. If n subjects answer the items this results in a binary data matrix Dwith m columns and n rows.Typical examples of this data format are test items which can be solved (1) or failed(0) by subjects. Other typical examples are questionnaires where the items arestatements to which subjects can agree (1) or disagree (0).Depending on the content of the items it is possible that the response of a subject to anitem j determines her or his responses to other items. It (en)
|
foaf:depiction
| |
dcterms:subject
| |
Wikipage page ID
| |
Wikipage revision ID
| |
Link from a Wikipage to another Wikipage
| |
Link from a Wikipage to an external page
| |
sameAs
| |
dbp:wikiPageUsesTemplate
| |
thumbnail
| |
has abstract
| - Item tree analysis (ITA) is a data analytical method which allows constructing ahierarchical structure on the items of a questionnaire or test from observed responsepatterns. Assume that we have a questionnaire with m items and that subjects cananswer positive (1) or negative (0) to each of these items, i.e. the items aredichotomous. If n subjects answer the items this results in a binary data matrix Dwith m columns and n rows.Typical examples of this data format are test items which can be solved (1) or failed(0) by subjects. Other typical examples are questionnaires where the items arestatements to which subjects can agree (1) or disagree (0).Depending on the content of the items it is possible that the response of a subject to anitem j determines her or his responses to other items. It is, for example, possible thateach subject who agrees to item j will also agree to item i. In this case we say thatitem j implies item i (short ). The goal of an ITA is to uncover suchdeterministic implications from the data set D. (en)
|
prov:wasDerivedFrom
| |
page length (characters) of wiki page
| |
foaf:isPrimaryTopicOf
| |
is Link from a Wikipage to another Wikipage
of | |
is Wikipage redirect
of | |
is foaf:primaryTopic
of | |