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Relapse Cases Among Drug Addicts Using Logistic Regression Modeling

机译:使用Logistic回归建模吸毒成瘾者中的复发案例

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The objective of this study is to use this statistical method to determine the factors which are considered to be significant contributors for relapse to happen. Logistic regression analysis is an important tool used in the analysis of the relationship between various explanatory variables and nominal response variables. There are eight predictors in this study. The predictors involved are gender, race, religious, age, level of education, type of drug, reason to drug, and technique to drug. The dependent variable is the status of the drug addict either relapses or not. Four hundred samples were randomly selected from National Anti-Drug Agency (NADA) in Kedah. The finding of the study revealed age and type of drug (Opiat) is highly significant. The coefficient of age and type of drug (Opiat) is 0.114 and 2.360. The older age increase the probability of drug addict to repeat. Type of drug indicates that drug addicts who use Opiat increase the probability to repeat compared to drug addict who use ATS (Amphetamine Type Stimulant (ATS). The findings are beneficial to reduce number of drug addict.
机译:本研究的目的是使用这种统计方法来确定被认为是复发发生的重要贡献者的因素。 Logistic回归分析是在分析各种解释变量和标称响应变量之间关系的重要工具。这项研究中有八个预测因素。所涉及的预测因素是性别,种族,宗教,年龄,教育水平,药物类型,药物的原因,以及药物的技术。受抚养变量是药物成瘾者的状态要么复发。四百个样品随机选自肯德国家抗药机(NADA)。该研究的发现揭示了药物(Apiat)的年龄和类型非常重要。药物的年龄和类型的系数(APIAIAIA)为0.114和2.360。年龄较大的年龄提高吸毒成瘾者重复的概率。药物类型表明,与使用ATS的吸毒成瘾者(Amphetamine型兴奋剂(ATS)的吸毒成瘾者相比,药物成瘾者增加了重复的概率。结果有利于减少吸毒成瘾的数量。

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