Pub Date : 2021-07-09DOI: 10.1080/08898480.2021.1941661
M. El Fatini, Mohamed El khalifi, R. Gerlach, R. Pettersson
ABSTRACT In a Covid-19 susceptible-infected-recovered-dead model with time-varying rates of transmission, recovery, and death, the parameters are constant in small time intervals. A posteriori parameters result from the Euler-Maruyama approximation for stochastic differential equations and from Bayes’ theorem. Parameter estimates and 10-day predictions are performed based on Moroccan and Italian Covid-19 data. Mean absolute errors and mean square errors indicate that predictions are of good quality.
{"title":"Bayesian forecast of the basic reproduction number during the Covid-19 epidemic in Morocco and Italy","authors":"M. El Fatini, Mohamed El khalifi, R. Gerlach, R. Pettersson","doi":"10.1080/08898480.2021.1941661","DOIUrl":"https://doi.org/10.1080/08898480.2021.1941661","url":null,"abstract":"ABSTRACT In a Covid-19 susceptible-infected-recovered-dead model with time-varying rates of transmission, recovery, and death, the parameters are constant in small time intervals. A posteriori parameters result from the Euler-Maruyama approximation for stochastic differential equations and from Bayes’ theorem. Parameter estimates and 10-day predictions are performed based on Moroccan and Italian Covid-19 data. Mean absolute errors and mean square errors indicate that predictions are of good quality.","PeriodicalId":49859,"journal":{"name":"Mathematical Population Studies","volume":"28 1","pages":"228 - 242"},"PeriodicalIF":1.8,"publicationDate":"2021-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/08898480.2021.1941661","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47451107","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-01DOI: 10.1080/08898480.2021.1915638
Li Qi, Min Hu, Lujie Chi, Jinpen Liao
ABSTRACT The total number of registered second children may be underestimated due to repetitions, omissions, and counting errors. The three-source estimator provides a more accurate value. It is based on the household registration list, a sample survey list, and the hospital birth list. It avoids the correlation bias inherent in the estimator based on a sample survey and household registration or hospital births. Its expression is adapted to the estimation of the total number of second children. In the case of Chengdu, it allows for estimating the total number of second children at 99,633, which is substantially higher than the reported number of 96,105 obtained by counting registrations alone.
{"title":"Estimated total number of second children based on three sources: the case of the city of Chengdu, Sichuan, China, for the year 2018","authors":"Li Qi, Min Hu, Lujie Chi, Jinpen Liao","doi":"10.1080/08898480.2021.1915638","DOIUrl":"https://doi.org/10.1080/08898480.2021.1915638","url":null,"abstract":"ABSTRACT The total number of registered second children may be underestimated due to repetitions, omissions, and counting errors. The three-source estimator provides a more accurate value. It is based on the household registration list, a sample survey list, and the hospital birth list. It avoids the correlation bias inherent in the estimator based on a sample survey and household registration or hospital births. Its expression is adapted to the estimation of the total number of second children. In the case of Chengdu, it allows for estimating the total number of second children at 99,633, which is substantially higher than the reported number of 96,105 obtained by counting registrations alone.","PeriodicalId":49859,"journal":{"name":"Mathematical Population Studies","volume":"29 1","pages":"1 - 16"},"PeriodicalIF":1.8,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/08898480.2021.1915638","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49536006","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-03-24DOI: 10.1080/08898480.2021.1893009
Z. Mielecka-Kubień, Mariusz Toniszewski
ABSTRACT The prevalence of illicit drug use among high school students living in the Silesian voivodship (Poland) is estimated using either the random response techniques of forced response design or the Liu-Chow method. Respondents answer a sensitive question only with a certain probability, thus ensuring anonymity. These methods provide correct estimates of prevalence, unlike interviews based on anonymous questionnaires, which can lead to underestimate the prevalence. Compared with those obtained with anonymous questionnaires, the results obtained with the forced response method are that 10.7 times more high school students used the new psychoactive substances, 6.0 times more amphetamines, methamphetamines, and others, 3.1 times more heroin or morphine, and 1.6 times more marijuana or hashish. The Liu-Chow method provides an estimate of 10.7% of respondents who reported using new psychoactive substances, while the estimate by the anonymous questionnaire is only 1.5%. In the case of marijuana or hashish, the Liu-Chow method gives an estimate of 37.0% of users, while the estimate with anonymous questionnaires is only 22.0%.
{"title":"Estimation of illicit drug use among high school students in the Silesian voivodship (Poland) with the use of the randomized response technique","authors":"Z. Mielecka-Kubień, Mariusz Toniszewski","doi":"10.1080/08898480.2021.1893009","DOIUrl":"https://doi.org/10.1080/08898480.2021.1893009","url":null,"abstract":"ABSTRACT The prevalence of illicit drug use among high school students living in the Silesian voivodship (Poland) is estimated using either the random response techniques of forced response design or the Liu-Chow method. Respondents answer a sensitive question only with a certain probability, thus ensuring anonymity. These methods provide correct estimates of prevalence, unlike interviews based on anonymous questionnaires, which can lead to underestimate the prevalence. Compared with those obtained with anonymous questionnaires, the results obtained with the forced response method are that 10.7 times more high school students used the new psychoactive substances, 6.0 times more amphetamines, methamphetamines, and others, 3.1 times more heroin or morphine, and 1.6 times more marijuana or hashish. The Liu-Chow method provides an estimate of 10.7% of respondents who reported using new psychoactive substances, while the estimate by the anonymous questionnaire is only 1.5%. In the case of marijuana or hashish, the Liu-Chow method gives an estimate of 37.0% of users, while the estimate with anonymous questionnaires is only 22.0%.","PeriodicalId":49859,"journal":{"name":"Mathematical Population Studies","volume":"29 1","pages":"47 - 57"},"PeriodicalIF":1.8,"publicationDate":"2021-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/08898480.2021.1893009","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"60023756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-03-01DOI: 10.1080/08898480.2021.1872230
A. Jafari, S. Bafekri
ABSTRACT Stress-strength reliability is a measure to compare the lifetimes of two systems. It is inferred for the two-parameter exponential distribution using generalized order statistics first without constraint on the location and scale parameters, second when the scale parameters are equal. A generalized confidence interval, bootstrap confidence intervals, a Bayesian interval, and a highest posterior density interval are computed for the stress-strength parameter. A Monte Carlo simulation shows that generalized confidence intervals provide more accurate average lengths of confidence intervals and higher probabilities to contain the true value of the parameter. Application: Confidence intervals for the time to remission of 20 leukemic patients treated with one of two drugs are approximately the same in most generalized statistical models. In addition, the time to remission for patients with the first drug is tested to be shorter than for patients with the second drug.
{"title":"Inference on stress-strength reliability for the two-parameter exponential distribution based on generalized order statistics","authors":"A. Jafari, S. Bafekri","doi":"10.1080/08898480.2021.1872230","DOIUrl":"https://doi.org/10.1080/08898480.2021.1872230","url":null,"abstract":"ABSTRACT Stress-strength reliability is a measure to compare the lifetimes of two systems. It is inferred for the two-parameter exponential distribution using generalized order statistics first without constraint on the location and scale parameters, second when the scale parameters are equal. A generalized confidence interval, bootstrap confidence intervals, a Bayesian interval, and a highest posterior density interval are computed for the stress-strength parameter. A Monte Carlo simulation shows that generalized confidence intervals provide more accurate average lengths of confidence intervals and higher probabilities to contain the true value of the parameter. Application: Confidence intervals for the time to remission of 20 leukemic patients treated with one of two drugs are approximately the same in most generalized statistical models. In addition, the time to remission for patients with the first drug is tested to be shorter than for patients with the second drug.","PeriodicalId":49859,"journal":{"name":"Mathematical Population Studies","volume":"28 1","pages":"201 - 227"},"PeriodicalIF":1.8,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/08898480.2021.1872230","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44703774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-02DOI: 10.1080/08898480.2021.1872944
Youngae Kim
{"title":"아픔이 길이 되려면: 정의로운 건강을 찾아 질병의 사회적 책임을 묻다 [When Pain Should be the Way: Social Responsibility Committed to the Pursuit of Righteous Health]","authors":"Youngae Kim","doi":"10.1080/08898480.2021.1872944","DOIUrl":"https://doi.org/10.1080/08898480.2021.1872944","url":null,"abstract":"","PeriodicalId":49859,"journal":{"name":"Mathematical Population Studies","volume":"28 1","pages":"61 - 62"},"PeriodicalIF":1.8,"publicationDate":"2021-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/08898480.2021.1872944","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47444463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-09DOI: 10.1080/08898480.2020.1855021
Guihua Hu, Shushan Fan, Jiwei Su, Lujie Chi, Jing Zhou
ABSTRACT Erroneous enumerations in the census include multiple enumerations and other errors. The linear estimator for estimating these errors currently used in several countries leads to underestimation when the sample used for the estimation comprises few of these errors. The “ratio estimator” of the total number of erroneous enumerations overcomes this difficulty. This is the one used by China for the 2020 census. Empirical analysis shows that the ratio estimator provides a smaller sampling error than the linear estimator.
{"title":"Estimation of erroneous enumerations in the census","authors":"Guihua Hu, Shushan Fan, Jiwei Su, Lujie Chi, Jing Zhou","doi":"10.1080/08898480.2020.1855021","DOIUrl":"https://doi.org/10.1080/08898480.2020.1855021","url":null,"abstract":"ABSTRACT Erroneous enumerations in the census include multiple enumerations and other errors. The linear estimator for estimating these errors currently used in several countries leads to underestimation when the sample used for the estimation comprises few of these errors. The “ratio estimator” of the total number of erroneous enumerations overcomes this difficulty. This is the one used by China for the 2020 census. Empirical analysis shows that the ratio estimator provides a smaller sampling error than the linear estimator.","PeriodicalId":49859,"journal":{"name":"Mathematical Population Studies","volume":"28 1","pages":"243 - 258"},"PeriodicalIF":1.8,"publicationDate":"2020-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/08898480.2020.1855021","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43587403","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-07DOI: 10.1080/08898480.2020.1827854
A. Naccarato, F. Benassi
ABSTRACT Taylor’s law states that the variance of population density in a given set of areas is a power function of its mean. When the exponent is equal to 2, the distribution of population densities between areas remains unchanged; when it is less than 2, the distribution converges toward the uniform distribution; when it is greater than 2, the densities become increasingly different from each other over time. The exponent takes the value 2 for East Asia, the Pacific, and South Asia. It takes a value greater than 2 for sub-Saharan Africa because the ongoing demographic transition and intense urbanization are redistributing the population over the territories. The exponent is lower than 2 for the other regions of the world, which have completed their demographic transition and where the rural exodus has been completed.
{"title":"World population densities: convergence, stability, or divergence?","authors":"A. Naccarato, F. Benassi","doi":"10.1080/08898480.2020.1827854","DOIUrl":"https://doi.org/10.1080/08898480.2020.1827854","url":null,"abstract":"ABSTRACT Taylor’s law states that the variance of population density in a given set of areas is a power function of its mean. When the exponent is equal to 2, the distribution of population densities between areas remains unchanged; when it is less than 2, the distribution converges toward the uniform distribution; when it is greater than 2, the densities become increasingly different from each other over time. The exponent takes the value 2 for East Asia, the Pacific, and South Asia. It takes a value greater than 2 for sub-Saharan Africa because the ongoing demographic transition and intense urbanization are redistributing the population over the territories. The exponent is lower than 2 for the other regions of the world, which have completed their demographic transition and where the rural exodus has been completed.","PeriodicalId":49859,"journal":{"name":"Mathematical Population Studies","volume":"29 1","pages":"17 - 30"},"PeriodicalIF":1.8,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/08898480.2020.1827854","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49270138","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-02DOI: 10.1080/08898480.2020.1816703
U. Shahzad, I. Ahmad, E. Oral, M. Hanif, I. Almanjahie
ABSTRACT Median ranked set sampling is a sampling procedure used to estimate the population mean when the variable of interest is difficult or costly to measure. Two estimators for the population mean based on the minimum and maximum values of the auxiliary variable are built upon a successive use of ranks, second raw moments, and the linearly transformed auxiliary variable. The biases and the mean square errors of the estimators are derived. The proposed estimators under median ranked set sampling have higher efficiencies than the ratio, regression, difference-cum-ratio, and exponential estimators.
{"title":"Estimation of the population mean by successive use of an auxiliary variable in median ranked set sampling","authors":"U. Shahzad, I. Ahmad, E. Oral, M. Hanif, I. Almanjahie","doi":"10.1080/08898480.2020.1816703","DOIUrl":"https://doi.org/10.1080/08898480.2020.1816703","url":null,"abstract":"ABSTRACT Median ranked set sampling is a sampling procedure used to estimate the population mean when the variable of interest is difficult or costly to measure. Two estimators for the population mean based on the minimum and maximum values of the auxiliary variable are built upon a successive use of ranks, second raw moments, and the linearly transformed auxiliary variable. The biases and the mean square errors of the estimators are derived. The proposed estimators under median ranked set sampling have higher efficiencies than the ratio, regression, difference-cum-ratio, and exponential estimators.","PeriodicalId":49859,"journal":{"name":"Mathematical Population Studies","volume":"28 1","pages":"176 - 199"},"PeriodicalIF":1.8,"publicationDate":"2020-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/08898480.2020.1816703","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47710847","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-07-20DOI: 10.1080/08898480.2020.1767926
H. M. Barakat, E. Nigm, I. A. Husseiny
ABSTRACT The Fisher information matrix related to an order statistic and its concomitant used to order a bivariate random sample are obtained in the case of the shape-parameter vector of an iterated Farlie–Gumbel–Morgenstern bivariate distribution. They contain information conveyed by singly or multiply censored bivariate samples drawn from an iterated Farlie–Gumbel–Morgenstern bivariate distribution. Fisher information is computed for the mean of the exponential distribution in the concomitant of an order statistic. Shannon entropy in the order statistics and their concomitants based on the iterated Farlie–Gumbel–Morgenstern bivariate distribution are derived.
{"title":"Measures of information in order statistics and their concomitants for the single iterated Farlie–Gumbel–Morgenstern bivariate distribution","authors":"H. M. Barakat, E. Nigm, I. A. Husseiny","doi":"10.1080/08898480.2020.1767926","DOIUrl":"https://doi.org/10.1080/08898480.2020.1767926","url":null,"abstract":"ABSTRACT The Fisher information matrix related to an order statistic and its concomitant used to order a bivariate random sample are obtained in the case of the shape-parameter vector of an iterated Farlie–Gumbel–Morgenstern bivariate distribution. They contain information conveyed by singly or multiply censored bivariate samples drawn from an iterated Farlie–Gumbel–Morgenstern bivariate distribution. Fisher information is computed for the mean of the exponential distribution in the concomitant of an order statistic. Shannon entropy in the order statistics and their concomitants based on the iterated Farlie–Gumbel–Morgenstern bivariate distribution are derived.","PeriodicalId":49859,"journal":{"name":"Mathematical Population Studies","volume":"28 1","pages":"154 - 175"},"PeriodicalIF":1.8,"publicationDate":"2020-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/08898480.2020.1767926","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42788920","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-07-02DOI: 10.1080/08898480.2018.1553413
X. Bry, Théo Simac, Salah Eddine El Ghachi, P. Antoine
ABSTRACT In event-history analysis with many possibly collinear regressors, Cox’s proportional hazard model, like all generalized linear models, can fail to be identified. Dimension-reduction and regularization are therefore needed. Penalty-based methods such as the ridge and the least absolute shrinkage and selection operator (LASSO) provide a regularized linear predictor, but fail to highlight the predictive structures. This is the gap filled by the supervised-component Cox regression (SCCoxR). Its principle is to compute a sequence of orthogonal explanatory components, which both rely on the strong correlation structures of regressors and optimize the goodness-of-fit of the model. One of its parameters tunes the balance between component strength and goodness of fit, thus bridging the gap between classical Cox regression with Cox regression on principal components. A second parameter allows the focus on subsets of highly correlated explanatory variables. A third parameter tunes the regularization of the model coefficients, leading to more robust estimates. Simulations show how to tune the parameters. The method is applied to the case study of polygamy in Dakar, Senegal.
{"title":"Bridging data exploration and modeling in event-history analysis: the supervised-component Cox regression","authors":"X. Bry, Théo Simac, Salah Eddine El Ghachi, P. Antoine","doi":"10.1080/08898480.2018.1553413","DOIUrl":"https://doi.org/10.1080/08898480.2018.1553413","url":null,"abstract":"ABSTRACT In event-history analysis with many possibly collinear regressors, Cox’s proportional hazard model, like all generalized linear models, can fail to be identified. Dimension-reduction and regularization are therefore needed. Penalty-based methods such as the ridge and the least absolute shrinkage and selection operator (LASSO) provide a regularized linear predictor, but fail to highlight the predictive structures. This is the gap filled by the supervised-component Cox regression (SCCoxR). Its principle is to compute a sequence of orthogonal explanatory components, which both rely on the strong correlation structures of regressors and optimize the goodness-of-fit of the model. One of its parameters tunes the balance between component strength and goodness of fit, thus bridging the gap between classical Cox regression with Cox regression on principal components. A second parameter allows the focus on subsets of highly correlated explanatory variables. A third parameter tunes the regularization of the model coefficients, leading to more robust estimates. Simulations show how to tune the parameters. The method is applied to the case study of polygamy in Dakar, Senegal.","PeriodicalId":49859,"journal":{"name":"Mathematical Population Studies","volume":"27 1","pages":"139 - 174"},"PeriodicalIF":1.8,"publicationDate":"2020-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/08898480.2018.1553413","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46077749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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