Banafsheh Yousefi, S. Lack, Seyed Mahmoud Tabib Ghaffary, A. Naderi, Mani Mojaddm
{"title":"IDENTIFICATION OF QUALITATIVE TRAITS IN SPRING WHEAT IN VERY LATE SOWING DATE AT KHUZESTAN (SOUTHWEST IRAN) HOT CLIMATE","authors":"Banafsheh Yousefi, S. Lack, Seyed Mahmoud Tabib Ghaffary, A. Naderi, Mani Mojaddm","doi":"10.17654/jb018030315","DOIUrl":"https://doi.org/10.17654/jb018030315","url":null,"abstract":"","PeriodicalId":40703,"journal":{"name":"JP Journal of Biostatistics","volume":" ","pages":""},"PeriodicalIF":0.1,"publicationDate":"2021-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47166209","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"APPLICATION OF PARAMETRIC MODELS TO A SURVIVAL ANALYSIS OF BREAST CANCER PATIENTS OF NORTH-EAST INDIA","authors":"S. Bhattacharjee, S. Deka","doi":"10.17654/jb018020295","DOIUrl":"https://doi.org/10.17654/jb018020295","url":null,"abstract":"","PeriodicalId":40703,"journal":{"name":"JP Journal of Biostatistics","volume":" ","pages":""},"PeriodicalIF":0.1,"publicationDate":"2021-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47810122","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"COMPARISON OF VARIABLE SELECTION METHODS FOR OPTIMIZING THE CALIBRATION OF CLINICAL PREDICTION MODEL","authors":"Y. Shiko, Y. Kawasaki","doi":"10.17654/jb018020269","DOIUrl":"https://doi.org/10.17654/jb018020269","url":null,"abstract":"","PeriodicalId":40703,"journal":{"name":"JP Journal of Biostatistics","volume":" ","pages":""},"PeriodicalIF":0.1,"publicationDate":"2021-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44081303","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Félix Almendra-Arao, M. Reyes-Reyes, M. Díaz-Arias
{"title":"JP Journal of Biostatistics","authors":"Félix Almendra-Arao, M. Reyes-Reyes, M. Díaz-Arias","doi":"10.17654/jb018030305","DOIUrl":"https://doi.org/10.17654/jb018030305","url":null,"abstract":"","PeriodicalId":40703,"journal":{"name":"JP Journal of Biostatistics","volume":" ","pages":""},"PeriodicalIF":0.1,"publicationDate":"2021-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43455076","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Randa Alharbi, D. Alnagar, A. T. Abdulrahman, O. Alamri
Background: The COVID-19 pandemic is an issue of global concern. It has been nine months since the first confirmed case of the coronavirus disease in Saudi Arabia. The recent COVID-19 outbreak has had a devastating impact on education, economic, stability and health. This study investigates the prevalence of anxiety and depression among individuals in Almadinh KSA during COVID-19. Method: A cross-sectional questionnaire was distributed to public in Amdadina KSA via Google forms collect the data. The responds included 78 female and 352 male, socio-demographic information including age, gender, and education levels was collected. Three mathematical models were determined to be powerful statistical techniques for classifying and predicting anxiety and depression: logistic regression, decision tree, and analysis. Results: The prevalence rates of anxiety and depression were 92.6 % and 91.4.0%, respectively. The decision tree and linear discriminate analysis yielded the same results. The accuracy of correctly classified cases was the same in all three methods. This analysis reveals significant structural differences between three methods. There is a wide range of Saudi citizens who are at higher risk for dysfunctional behavior during COVID-19 pandemic.
{"title":"STATISTICAL METHODS TO REPRESENT THE ANXIETY AND DEPRESSION EXPERIENCED IN ALMADINH KSA DURING COVID-19","authors":"Randa Alharbi, D. Alnagar, A. T. Abdulrahman, O. Alamri","doi":"10.17654/JB018020231","DOIUrl":"https://doi.org/10.17654/JB018020231","url":null,"abstract":"Background: The COVID-19 pandemic is an issue of global concern. It has been nine months since the first confirmed case of the coronavirus disease in Saudi Arabia. The recent COVID-19 outbreak has had a devastating impact on education, economic, stability and health. This study investigates the prevalence of anxiety and depression among individuals in Almadinh KSA during COVID-19. Method: A cross-sectional questionnaire was distributed to public in Amdadina KSA via Google forms collect the data. The responds included 78 female and 352 male, socio-demographic information including age, gender, and education levels was collected. Three mathematical models were determined to be powerful statistical techniques for classifying and predicting anxiety and depression: logistic regression, decision tree, and analysis. Results: The prevalence rates of anxiety and depression were 92.6 % and 91.4.0%, respectively. The decision tree and linear discriminate analysis yielded the same results. The accuracy of correctly classified cases was the same in all three methods. This analysis reveals significant structural differences between three methods. There is a wide range of Saudi citizens who are at higher risk for dysfunctional behavior during COVID-19 pandemic.","PeriodicalId":40703,"journal":{"name":"JP Journal of Biostatistics","volume":" ","pages":""},"PeriodicalIF":0.1,"publicationDate":"2021-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42292778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Due to the COVID-19 outbreak which showed its deadly results all around the world in the first quarter of 2020, all the countries have taken different measures. It is planned with lockdown, which has been a primary measure, to minimize human contact and decrease transmission rates. Various lockdown measures have been taken and implemented in different regions of Turkey, too. This research studies the effect of the change in densities in different locations on COVID-19 health data, based on the mobility trends in a certain time period and COVID-19 health data obtained regarding the related time period in Turkey. Thus, it is shown that decreasing the mobility trend has a positive effect on statistics concerning human life.
{"title":"A REVIEW ON THE COVID-19 EFFECTS OF THE MOBILITY TRENDS","authors":"Ö. Başar, Seda Bağdatlı Kalkan","doi":"10.17654/JB018020149","DOIUrl":"https://doi.org/10.17654/JB018020149","url":null,"abstract":"Due to the COVID-19 outbreak which showed its deadly results all around the world in the first quarter of 2020, all the countries have taken different measures. It is planned with lockdown, which has been a primary measure, to minimize human contact and decrease transmission rates. Various lockdown measures have been taken and implemented in different regions of Turkey, too. This research studies the effect of the change in densities in different locations on COVID-19 health data, based on the mobility trends in a certain time period and COVID-19 health data obtained regarding the related time period in Turkey. Thus, it is shown that decreasing the mobility trend has a positive effect on statistics concerning human life.","PeriodicalId":40703,"journal":{"name":"JP Journal of Biostatistics","volume":" ","pages":""},"PeriodicalIF":0.1,"publicationDate":"2021-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42682005","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Fayaz, Alireza Abadi Soheila Khodakarim, M. Hoseini, A. Razzaghi
{"title":"THE DATA-DRIVEN PATTERN FOR HEALTHY BEHAVIORS OF CAR DRIVERS BASED ON DAILY RECORDS OF TRAFFIC COUNT DATA FROM 2018 TO 2019 NEAR AIRPORTS: A FUNCTIONAL DATA ANALYSIS","authors":"M. Fayaz, Alireza Abadi Soheila Khodakarim, M. Hoseini, A. Razzaghi","doi":"10.17654/bs017020539","DOIUrl":"https://doi.org/10.17654/bs017020539","url":null,"abstract":"","PeriodicalId":40703,"journal":{"name":"JP Journal of Biostatistics","volume":" ","pages":""},"PeriodicalIF":0.1,"publicationDate":"2020-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45692162","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-26DOI: 10.20944/preprints202010.0522.v1
D. Arku, G. Kallah-Dagadu
The purpose of this study is to estimate the mean transitioning probabilities from a Healthy state to malaria positive uncomplicated state or to malaria positive severe state. It also classifies the various transitioning probabilities of moving through the various states based on some baseline characteristics. Malaria test results for 2019 over a 12-month period were collected from the University of Ghana school clinic. An H-U model for the study was developed and the transition rates from the cross-sectional data are indicated. With two states Healthy (H) and Uncomplicated (U) forming a state space, there were four possible transitions. The results show that the probability of transitioning from a Healthy state to a malaria positive state is 0.03% while the probability that an individual will remain at Healthy state (H) after the test is 99.73%. It was found that if an individual is already positive and has taken medication the probability that its second test came out negative is 6.45% while the chances that it will remain positive but uncomplicated is 93.55%. The study also showed that in the long run, about 95.98% of persons who visited the student clinic with malaria symptoms recorded negative tests for malaria parasite while about 4% recorded positive for malaria. In terms of disaggregation by gender, it was realized that the number of reported negative test results were higher for females (97.08%) than for males (96.13%). However, the infection rate is higher for males (3.87%) than females (2.92%). It is recommended that in as much as the University of Ghana has two health centers (a clinic and hospital), there should be a centralized system to track students’ health so research done would not be biased.
{"title":"A Stochastic H-U Model for Malaria Transmission via Markov Theory","authors":"D. Arku, G. Kallah-Dagadu","doi":"10.20944/preprints202010.0522.v1","DOIUrl":"https://doi.org/10.20944/preprints202010.0522.v1","url":null,"abstract":"The purpose of this study is to estimate the mean transitioning probabilities from a Healthy state to malaria positive uncomplicated state or to malaria positive severe state. It also classifies the various transitioning probabilities of moving through the various states based on some baseline characteristics. Malaria test results for 2019 over a 12-month period were collected from the University of Ghana school clinic. An H-U model for the study was developed and the transition rates from the cross-sectional data are indicated. With two states Healthy (H) and Uncomplicated (U) forming a state space, there were four possible transitions. The results show that the probability of transitioning from a Healthy state to a malaria positive state is 0.03% while the probability that an individual will remain at Healthy state (H) after the test is 99.73%. It was found that if an individual is already positive and has taken medication the probability that its second test came out negative is 6.45% while the chances that it will remain positive but uncomplicated is 93.55%. The study also showed that in the long run, about 95.98% of persons who visited the student clinic with malaria symptoms recorded negative tests for malaria parasite while about 4% recorded positive for malaria. In terms of disaggregation by gender, it was realized that the number of reported negative test results were higher for females (97.08%) than for males (96.13%). However, the infection rate is higher for males (3.87%) than females (2.92%). It is recommended that in as much as the University of Ghana has two health centers (a clinic and hospital), there should be a centralized system to track students’ health so research done would not be biased.","PeriodicalId":40703,"journal":{"name":"JP Journal of Biostatistics","volume":" ","pages":""},"PeriodicalIF":0.1,"publicationDate":"2020-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44749159","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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