APPLICATION OF 0-1 NORMALIZED PRINCIPAL COMPONENT TO:GROBAL EVALUATION OF APHASIC SYMPTOMS
スポンサーリンク
概要
- 論文の詳細を見る
Principal component analysis was applied to summarize test errors in 46 items of the Minnesota Test for Differential Diagnosis of Aphasia into an one-dimensional value. To avoid data dependency of principal components, an attempt was made to normalize the principal components from minimum 0.0 to maximum 1.0 and formalized as f;01=n∑i=1aixi/n∑i=1aiximax. where ai=li/√V(xi), the li is the first characteristic vector of the correlation matrix, and xi, ximax and V(xi)are errors, possible errors and variance of the ith item of the test respectively. This normalzied component was referred to as"0-1 score"which was also formalized as f;01=nΣi=1βixi, whereβi=ai/nΣi=1aiximax and n=46, the number of items to be analyzed. 0-1 score was applied to 176 aphasics and revealed: 1)0-1 score coefficient β i was considered to be stable regardless the samples by which correlation matrices was computed. 2)Correlation coefficient between 0-1 scores and scores of clinically evaluated overall daily-life-speech-activity was high(γ =0.91). 3)Values of0-1 score by the Minnesota Classification of aphasia were thought to be compatible to clinical impression of severity of aphasia. From these results, 0-1 score is a proper measure to summarize test data of the Minnesota Test for Differential Diagnosis of Aphasia to an one-dimensional numerical value and appers to be one of good method for evaulation of aphasia.
- 日本行動計量学会の論文
日本行動計量学会 | 論文
- 2. Bayesian Generalized Bradley-Terry Model using RJMCMC
- 予測変数を伴う展開型項目反応モデル(一般セッション IRT)
- 刺激が複数の要因の影響下にあるときの尺度構成法 : Bradley-Terryモデルを用いて(セッションN-11(MK202) 一般セッション 心理2)
- プログラミング演習支援のためのコンパイルエラー分析(e-learning・e-testing)
- 4.問題解決力を涵養する統計教育支援教材の研究開発(特別セッション 問題解決力を育む統計教育の展開)