Model Survival Semiparametrik dan Parametrik Kasus Data Demam Berdarah
DOI:
https://doi.org/10.23887/jstundiksha.v11i2.43493Keywords:
Analisis survival, DBD, Cox PH, Breslow, Efron, exactAbstract
Data survival merupakan bagian dari time-to-event data. Data survival adalah data longitudinal dimana subjek dipantau dan diikuti dari awal permulaan hingga hingga subjek tersebut mengalami peristiwa yang diinginkan. Demam Berdarah Dengue (DBD) merupakan penyakit infeksi yang disebabkan oleh virus dengue, yang ditularkan dari nyamuk Aedes Spp. Penanganan pasien DBD dengan karakteristik yang dimilikinya perlu dikaji agar untuk mendapatkan informasi dan mengambil langkah yang tepat. Salah satu upaya dari sisi pemodelan adalah dengan menganalisis daya taha (survival) pasien DBD. Penelitian ini bertujuan untuk menganalisis performa model survival parametrik dan semiparametric pada kasus DBD. Metode estimasi Breslow, Efron, dan Exact merupakan pilhan estimasi parameter karena dapat menangani kasus waktu kejadiann kembar (ties). Pemilihan performa model erbaik didasarkan pada Akaike Information Criteria (AIC). Hasil analisis menunjukkan bahwa model terbaik yang diperoleh adalah model semiparametrik Cox PH dengan metode estimasi Exact. Berdasarkan model ini ditemukan bahwa pasien dengan karakteristik berusia lebih muda, kadar hematokrit rendah, kadar hemoglobin tinggi, kadar leukosit rendah , dan suhu badan rendah memiliki laju kesembuhan yang lebih besar dibandingkan dengan pasien dengan karakteristik sebaliknya.
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