REGRESI LOGISTIK: MENAKSIR PROBABILITAS PERISTIWA VARIABEL BINARI
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Abstract
Prediksi melalui suatu pemodelan statistic merupakan kekuatan utama dari analisis regresi linier. Akan tetapi, teknik ini mensyaratkan variabel dependen atau kriteria harus memiliki data kontinum dan sebaran skor yang normal sehingga ia tidak dapat digunakan jika variabel kriterianya merupakan variabel binary (nominal dengan dua kategori, memiliki skor 1 atau 0). Regresi logistik merupakan teknik yang tepat untuk menggantikannya. Alih-alih menghasilkan taksiran skor variabel kriteria, pemodelan dengan regresi logistik menghasilkan taksiran probabilitas munculnya peristiwa (skor 1) pada variabel kriteria. Taksiran probabilitas tersebut diperoleh melalui model regresi yang menghasilkan nilai odds dan log odds, yang pada dasarnya merupakan cara pengungkapan yang berbeda tentang kenyataan yang sama terkait taksiran probabilitas munculnya peristiwa dari seluruh kejadian dalam variabel kriteria.
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