MPhil Thesis

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Statistical Analysis of the Average Life of Electric Bulbs: A Comparative Study
(University of Rajshahi, 1991) Islam, Md. Aminul; Mian, Md. Abul Basher
This thesis -- 'Statistical Analysis of the Average Life of Electric Bulbs: A comparative study' consists of six chapters of which chapter four and five are contributory, chapter six on the summary conclusion of the thesis. First three chapters of the thesis are introduction and discussions on the selection of a life testing model and the underlying methods of statistical inferences which has been used in the subsequent chapters towards the contribution in the' thesis. The introductory chapter one contains a statement of the problem we have undertaken a brief review of earlier studies and exploration of the possibilities of further work in relation to the present study, aims and scope of the study. It also provides a brief discussion on the concept of life testing and reliability and distributions of life times. A survey of some basic life testing models which has been used in contributory chapters has also been appended in this chapter. Chapter two of this thesis is devoted on discussions on the selection of a. life testing model to suit the analysis and prediction for a particular set of data. Almost all life testing data available for analysis and prediction are incomplete or censored. Most of the tools and techniques available in life testing literature for discriminating between competing life testing models are sensitive to the nature and size of censoring……………………..
Modelling of Diabetes Mellitus Data
(University of Rajshahi, 2002) Sultana, Mst. Papia; Mian, M.A. Basher
Diabetes afflicts a large number of people of all social conditions throughout the world. So, it is a major health problem of all the countries of the world including Bangladesh. Inspite of increasing advances in the past several years in almost every field of diabetes research and patient care, the personal and public health problem of diabetes, already of vast proportion, continuously increasing day by day. The scale of the problem that diabetes poses to world health is still widely under recognized. Recent estimates predict that if current trends continue the number of persons with diabetes will be more than double, from 140 million to 300 million in the next 25 years. The greater proportion of the increase is likely to occur in the developing countries, which are the communities who can least afford it [Source: http://www.who.int/ncd/dia/index.htm]. Bangladesh also possess the same picture. Surveys conducted by DAB ( 1995) reveals that the number of diabetic patients in Bangladesh is 1 to 1.5 percent of the total population. The rate is higher in the urban and industrial areas, perhaps the cause is to adequate physical work of rural areas.
The Role of High Leverage Points in Regression Diagnostics
(University of Rajshahi, 2003) Khan, Md. Ashraful Islam; Imon, A. H. M. Rahmatullah
In fitting a linear regression model by the least squares’ method, leverage values play a very important role. They often fo1m the basis of regression diagnostics as measures of influential observations in the explanatory variables. Much work has been done on the detection of high leverage values and a good number of diagnostic measures are now available in the literature. But neither of these methods is effective in the identification of high leverage points when multiple high leverage points are present in the data. In our study we proposed a new method for the identification of multiple high leverage points. The usefulness of this newly proposed method is studied under a variety of leverage structures through Monte Carlo simulation experiments. We also investigated the performance of the newly proposed method as a remedy to multi collinearity problem caused by the presence of multiple high leverage points.
Modeling of Development and Carbon Dioxide Emission in Bangladesh: A Bootstrap Approach
(University of Rajshahi, 2006) Sharker, Md. Abu Yushuf; Nasser, M.; Razzaque, M. A.
In the thesis we study the relationship between CO2 emission per capita and GDP per capita in context of Bangladesh. First, exploratory data analysis (EDA) is used to uncover the hidden information carried by the observed data. Au attempt is made to fit Environmental Kuznets Curve model by means of classical techniques as well as bootstrap techniques. EDA shows that both CO2 Emission per capita and GDP per capita are trended. There is no steady state of the variables within their sample period. This variable does not follow EKC. To test the presence of stochastic trend of the variables we use unit root tests. To mitigate small sample limitations of our data we first design a simulation based study to compare the performance of classical tests with bootstrap tests. Our simulation based result provides that CADF (Covariate Augmented Dickey Fuller Test) test has higher power and BCADF (Bootstrapped CADF) test has less size distortion for testing unit root for small sample of size 30. Unit root tests suggest that both the series are non stationary, i.e., CO2 is accumulating in the atmosphere and GDP is also experiencing accumulation. In the succession of time series modeling ARIMA model is fitted to both of the series. Both CO2 emission per capita and GDP per capita of Bangladesh follow ARIMA (0, 1, 1) model. Forecasting by bootstrap produces better results sometimes. In quest of dynamic regression model co integration is checked. Classical, bootstrap and double bootstrap techniques are used to test whether there exists any co integrating relationship among CO2 emission per capita, GDP per capita and it's square. Result shows that these variables are non stationary but not co integrated. There exists no long run equilibrium relationship between CO2 emission per capita and GDP per capita.
Anthropometric Study of the Shantal Community in Rajshahi District
(University of Rajshahi, 2006) Karim, Md. Rezaul; Islam, Md. Nurul; Ali, Md. Ayub
The aim of the thesis was to study Anthropometric variables sta􀀊ure, body weight, body mass index (BMI), sitting height and chest circumference, to find their relationships with some of the demographic and Socio-economic variables of Shantal community in Rajshshi District, Bangladesh. The_demographic and socioeconomic variables were collected through a questionnaire (in Appendix-I). Anthropometric measurements were taken by the· author himself. The cluster sampling technique was applied. The sample size were 396 for male and 438 for female. The present study demonstrated that the average stature, body weight, sitting height and chest circumference of young Shantals were increasing comparatively with those of oldest Shantals. Almost every Shantals were very lean and thin and stature, body weight, sitting height, and chest circumference of Shantals were positively and significantly related to each other. The present study indicated that the female onset of menarche of Shantals community reached earlier who were heavier and became late menarche who were both taller and thinner. Also lower BMI of female Shantals were reached age at menarche earlier than those of larger BMI. Also, age at menarche was earlier for those whose family income were higher and was late for those whose family income were lower and the onset of menarche reached earlier than those who have fewer number of sibling. Through the logistic regression, the present study suggest that the stature of literate male Shantals were shorter than the stature of illiterate Shantals and their differences were signHicant (p<0.05). The body weight and occupation were negatively associated but their differences were insignificant. The stature of literate female Shantals were higher than the stature of illiterate female Shantals and the body weight of female labors were lower than the body weight of non-labor female Shantals with significant differences. Sexual differences among stature, body weight and BMI of Shantals were found and the male Shantals were taller in stature and heavier in body weight than female Shantals and female Shantals were lean and thin. Government should take favorable view and necessary co-operations for their better health, social and economic management.
Robust Diagnostic Deletion Techniques in Linear and Logistic Regression
(University of Rajshahi, 2008) Nurunnabi, Abdul Awal Md.; Nasser, Mohammed
Identification of unexpected observations is a topic of great attention in modem regression analysis. At the beginning statisticians differ but now they recognize robust regression and regression diagnostics are two complementary remedies to study unusual observations. We use both of them for identifying irregular observations at a time. We find out the group deletion diagnostic methods that show better performance for identifying influential observations in linear regression. These are based on robust regression and/or relevant diagnostic methods so that these are free from huge computational tasks and reliable in presence of masking and/or swamping because of prior suspect-group identification. We find a technique that performs well in case of large number and high-dimensional data sets. We have done a classification task of unusual observations in linear regression according to their nature of consequences on the analysis, and model building process. At the same time the method performs well for identifying influential observations. This method may be a good addition to the existing graphical literature. We have seen that our proposed procedures in linear regression are also effective to the logistic regression after some modification and development to the existing identification techniques in linear regression. Our further contribution is to propose two new identification techniques for influential observations in logistic regression. The new methods show efficient performance for the proper identification of unusual observations and thereby provide less misclassification error in the response variable for the binomial logistic regression. Summarizing all the above issues we can say that we have made contribution in three areas: identification of influential observations in linear regression, classification of unusual observations in linear regression, and identification of unusual observations in logistic regression.
Factors Affecting Infant and Child Mortality in Bangladesh: A Multivariate Analysis
(University of Rajshahi, 2008) Islam, Md. Mogibul; Islam, Md. Nurul
The reduction of infant and child mo11ality in the developing countries is one or the most substantial achievements of human kind. However, in spite of various effective intervention programs, the infant and child mortality are considerably high in Bangladesh. Therefore, in this study, an attempt has been made to assess the levels, patterns and determinants of mortality in Bangladesh utilizing nationally representative data from Bangladesh Demographic and Health Survey (BDHS) 2004. The purpose of this study is also to identify user-related factors, which influence the infant and child mortality in Bangladesh. Differential pattern in infant and child mortality in Bangladesh is examined using bi variate analysis, logistic regression analysis and also factor analysis in multivariate approach. The study results show that several socioeconomic, demographic and household variables affect infant and child mortality. These are: place of residence, division, mother's education, father's education, father's occupation, age of mother at birth of child, sex of child, preceding birth interval, availability of electricity, sources or drinking water, toilet facilities, exposure to mass media i.e., radio, TV and floor/wall/roof materials. Multivariate analysis results indicate that type of place of residence, sex of child, mother's education, father's occupation and division are important factors that have significant influence on infant and child mortality. Ti1e most significant predictors of neonatal, post-neonatal and infant mortality are mother's education and father's occupation. Father and mother's education both are persistent socioeconomic predictors of mortality. Construction materials of wall of houses are found significant for neonatal mortality. Floor materials are found significant for infant mortality. Furthermore, differential analysis shows that, male children experienced substantially higher mortali1y than female children did at neonatal, infantile and child periods but in post-neonatal period the relationship is opposite.
Pattern of Migration in Joypurhat District of Bangladesh: A Case Study
(University of Rajshahi, 2010) Talukder, Md. Ashraful Alom; Hossain, Md. Ripter; Rahman, Md. Mostafizur
This study is based on primary data. The primary data were collected from Joypurhat district by PPS sampling method. The main purpose of this study is to identify the effects of demographic and socio-economic variables on rural migration, trends and volume of migration and constructed some probability models on such data in J oypurhat district, Bangladesh. Both unvaried and multivariate techniques have been used to study the differentials and determinants of migration. The study reveals that the migration rate was found significantly higher for the people age groups 15-29 (about 28 per cent). The age distribution of migrants clearly shows that majority of them were very young at the time of their first migration. Education of migrants show that the 58 per cent of migrants were passed both SSC to graduate and above. The pre-migration occupation are 41 per cent of migrants were involved with studies, but after migration it was found 48 per cent of migrants were employed in job/service. In study area we found that about 44 per cent of migrants were migrated in Dhaka city. We also observed that more than 51 per cent of migrants were migrated with influencing of their family members (puss factor) and it is remarkable that about 74 per cent of migrants were migrated due to job/service at a particular place of destination(pull factor). The findings indicate that the variables 'education', 'occupation', and 'family size' included in the analysis have had significant effect on rural out-migration. The risk of out-migration was remarkably higher for the households whose member(s) attained at least primary education and the risk of out-migration was significantly higher for the household with occupation as non-agricultural labour. The multivariate logistic regression analysis has been used to identify the determinants of out-migration at household level. The risk of migration was 1.85, 5.00, 10.83 and 10.69 times higher for the households with educational level- primary, secondary, SSC/HSC (secondary school certificate/higher secondary certificate) and graduate respectively as compared to households with no education. The volume of migration showed that a positive relationship with diversity of social status(.307), education(.373) and occupation(.539). Only the education and occupation diversity have been found to be significantly related with volume of outmigration. The migration model proposed by Sivamurthy and Kadi (1984) were found suitable to describe the volume of out-migration for Bangladesh. Finally, we found that the probability distribution under such assumptions fitted well. The distribution of male migrants aged 15 years and above and the probability model have been worked out to describe the distribution of households according to total number of migrants under different assumptions.
A Study of Some Non-linear Stochastic Models on Renewable Resources Management: Application to Forestry
(University of Rajshahi, 2010) Hossain, Md. Mowazzem; Shah, Md. Asaduzzaman
Management is a vibrant and multi phase dynamic process, just like social, scientific and engineering processes, that involves a wide spectrum of activities such as planning, coordination, communication, policy framing, decision making and their implementation. During the last three decades, the management of natural resources in general and that of renewable resources, in particular, has invited the attention of a large segment of researchers in various field [1-SJ. In order to maintain the ecological balance, as well as, meet the economic needs, the forest can play a vital role. Our government also taking special initiative to can-y forward a forestation program throughout the country. Also, to pollution free environment a forestation has no alternative. In this direction government organizations came forward to utilize the renewable resources for economic prosperity of the nation.
Allometric Model Study of Inter Limb Growth: A Case Study of Children From Jessore District
(University of Rajshahi, 2010) Nawaz, Md. Shahjada Ali; Ali, Md. Ayub
The aim of this study was to investigate the allometric growth of inter-limbs of males and females. All the subjects were student of primary school of urban and rural area at Jessore district in Bangladesh. The age ranges of the subjects were between 6 to 12 years for males, 6-11 years for females. Longitudinal data on body and head dimensions (stature, weight, sitting height, leg length, chest circumference, left and right upper arm length, elbow-wrist length, left and right tibia length, left and right upper arm circumference, head length, head breadth and head circumference) were measured from 2006 to 2009. The study started with 117 children. There was about 24% loss of the sample size. Finally we were 89 subjects. Descriptive statistics, growth chart and allometric growth model were used. Allometric relationships between body and head dimensions were obtained through log-linear regression analysis. Growth of head dimensions (head length, head breadth and head circumference) was negatively allometric with respect to stature for males and females, i.e., growth rate of head dimensions were smaller than growth rate of stature. Growth of body dimensions (leg length, tibia length, arm length etc.) were positive allometry with respect to stature implying growth of these body dimensions were greater than that of stature but the growth of sitting height with respect to stature were negative allometry. Growth of leg length and upper arm length with respect to stature were isometry for urban females. Growth of urban males and females were greater than rural males and females in stature, weight, sitting height, leg length, chest circumference, head length, head breadth and head circumference. Average stature differs more than 5 cm between urban and rural females, 4 cm for urban males and females. Average weight differs more than 4 kg between urban and rural males, 6 kg for urban and rural females. An in-depth further study should be taken into accounts for searching the reason of this regional difference.
Investigating the Trend and Impact of Some Variables on HYV Boro Rice Production in Northern Region of Bangladesh
(University of Rajshahi, 2011) Kundu, Ranjan Kumar; Karmokar, Provash Kumar
Boro rice is playing a significant role in the total rice production of Bangladesh. High yielding variety (HYV) Boro rice is grown enormously in the Northern region of Bangladesh. On the basis of per hector production, three HYV Boro rice producing districts have been selected by Simple Random Sampling for the present study. The selected three districts are Rajshahi, Rangpur and Dinajpur. To fulfill the objectives of the present study Trend Analysis and Factor Analysis have been anticipated. Suitability of commonly used trend models like Linear, Compound and Quadratics trend models for the selected districts were checked by Mann-Kendall and Spearman non parametric statistical tests and parameters of these models were estimated by OLS technique. The DW statistics are obtained by OLS technique shows the evidence of autocorrelation in the data sets. To overcome this problem we have used CochraneOrcutt technique to estimate of parameter of the trend models. The Cochrane-Orcutt technique minimizes the autocorrelation problem. The JB test shows the normality assumption of errors for all the models. Although the R2 and adjusted R2 have increased for all the models it is remarkable of about 17%-18% increasing of these values for Rajshahi districts in both the Linear and Compound models. The HYV Boro productions of the selected districts have been forecasted up to year 2021 for three trend models using the data from 1971 to 2003 by Cochrane-Orcutt technique and the results are given in detailed in Chapter Three. It is seen from the result that the Compound Trend model performs better maintaining the growth rate 1.009 for Rajshahi, 1.012 for Rangpur, 1.008 for Dinapur and its forecasting performance is the best among the trend models. Production of HYV Boro rice may depend on several climatic and non climatic variables like, rainfall, temperature, wind speed, humidity, cloud coverage, CO2 emission, fertilizer use and tractor use. In this study, we are also interested to identify the factors whose impacts are influential to the HYV Boro production of the selected districts of northern region of Bangladesh. Factor analysis, a data reduction technique have been used to identify the impact such variables on HYV Boro rice production in northern region of Bangladesh. Our analysis has identified five influential factors for the HYV Boro rice production for each of the districts. Therefore it is shown that the selected factors account for 82.33% of the total variance for Rajshahi district, 75. 71 % of the total variance for Rangpur district and 71.57% of the total variance for Dinajpur districts. The findings of this study convey a message to the agriculturist, concerned authorities and policy makers that keep watching of climatic factors and proper handling of other relevant factors in Boro rice production of northern region that would be significant in food supplying in this region and enhance the food security of Bangladesh.
Study of Potential Impacts of Climate Change on Food Production in Bangladesh
(University of Rajshahi, 2013) Chowdhury, Md. Mizanur Rahman; Rahman, M.Sayedur; Hossain, M. Ripter
The climate plays significant role in the agriculture of a country. The Rajshahi region is the driest part of the country in terms of rainfall. Rainfall is the most important weather parameter affecting non-irrigated crop areas. Water deficits and excess water are the greatest constraints for rain fed rice yields in this region. The daily rainfall data for 30 years during the period 1981-2010 of the station Rajshahi, Barisal and Comilla district in region are considered in this study. This study also considered weekly rainfall for 2.5mm and 5mm. The daily data were reduced in the weekly form and the drought index has been calculated using the probability of Markov chain model. Drought is temporary but complex feature of the climate system. Agriculture drought is mainly concerned with inadequacy of rainfall. Markov chain model have been used to evaluate probabilities of getting a sequence of wet-dry weeks over this region. An index best on the parameters of this model has been suggested for agriculture drought measurement in this region. The results indicate that the drought index for rainfall 2.5mm of rain for Rajshahi district annual is Mild, pre-kharif are Mild, Occasional, and Moderate, kharif is Occasional and Rabi is Chronic. The drought index for rainfall 5mm of rain for Rajshahi district annual is Mild, pre-kharif are Mild, Occasional and Moderate, kharif is Occasional and Rabi is Chronic. The drought index for rainfall 2.5mm of rain for Barisal district annual is Mild, pre-kharif are Mild, Occasional and Mild, kharif is Occasional and Rabi is Chronic. The drought index for rainfall 5mm of rain for Barisal district annual is Mild, pre-kharif is Occasional, kharif is Occasional and Rabi is Chronic. The drought index for rainfall 2.5mm of rain for Comilla district annual is Mild, pre-kharif are Mild, Occasional, Mild and Moderate, kharif is Occasional and Rabi is Chronic. The drought index for rainfall 5 mm of rain for Comilla district annual is Occasional, and Mild, pre-kharif are Mild, Occasional and Mild, kharif is Occasional and Rabi is Chronic. As a result, failure to rains and the occurrences of drought during any particular growing season lead to severe food shortages. A Markov chain model is established to fit daily rainfall data for the various aspects of rainfall occurrence patterns and could be mathematically derive from the Markov Chain by maximum likelihood estimate and these were also established to fit the observed data .The distribution of the number of success is asymptotically normal. The rainfall probability was not found to very much during rabi (November- February) season. But much more variation of rainfall probabilities was observed during both kharif (June-October) and pre-kharif (March- May) seasons. Obviously, one would presume conditions variation in these probabilities also yearly, seasonally and annually. Based on these findings and using chi-square test, it could be concluded that the model fit was good. This study investigates the methods to obtain estimates of the conditional probabilities, the probability of success and its probability distribution to describe the yearly, seasonal and annual variability. The limited data set the results are quite good and the model is doing a reasonably good job of daily rainfall. The probability can be used for both instantaneous and climate time scale retrievals. As the distribution of number of success asymptotically normal, it is playing a vital role for important decisions such as disaster prevention preparedness strategy. This study will contribute toward a better understanding of the climatology of drought in major monsoon region of the world. The findings of this study will be helpful for every researcher.
Analysing the Variability of Rainfall Threshold Values for Drought Prognosis in Bangladesh
(University of Rajshahi, 2013) Alam, Md. Mahbub; Rahman, M. Sayedur; Hossain, Md. Ripter
The Rainfall plays a significant role in the agriculture of country. Rainfall is the most important weather parameter affecting non-irrigate crop areas for Bogra, Jessore and Feni water deficits and excess water are the greatest constraints for rainfall rice yields in this region. The daily rainfall data for 30 years during the period 1981-2010 of the rainfall stations in Bogra, Jessore and Feni are considered in this study. The daily data were reduced in the weekly form and the drought index has been calculated using the probability of Markov chain model. Drought is temporary but complex feature of the climate system. Agricultural drought is mainly concerned with inadequacy of rainfall. Markov chain model have been used to evaluate probabilities of getting a sequence of wet-dry weeks over this region. An index based on the parameters of this model has been suggested for agricultural drought measurement in this region. The results of our Bogra district annually rainfall data we observed the moderate drought, pre-kharif rainfall data we observed the mild occasional and moderate drought, kharif rainfall data we observed the occasional and rabi rainfall data we observed the chronic prone. As a result failure of rains and the occurrence of drought during any particular growing season lead to severe food shortages. A Markov Chain model is established to fit daily rainfall data for the various aspects of rainfall occurrence patterns and could be mathematically derived from the Markov Chain by using maximum likelihood estimate and these were also established to fit the observed data. The rainfall probability was not found to very much during rabi (November- February) season. But much more variation of rainfall probabilities was observed during both kharif (June-October) and pre-kharif (March- May) seasons. Obviously, one would presume conditions variation in these probabilities also yearly, seasonally and annually. Based on these findings and using chi-square test, it could be concluded that the model fit was good. This study investigates the methods to obtain estimates of the conditional probabilities, the probability of success and its probability distribution to describe the yearly, seasonal and annual variability. The limited data set the results are quite good and the model is doing a reasonably good job of daily rainfall.
Study of Climate Variability and Agriculture Drought in Bangladesh
(University of Rajshahi, 2013) Matin, Md. Abdul; Rahman, M. Sayedur; Hossain, Md. Ripter
The climate plays significant role in the agriculture of a country. Rainfall is the most important climate parameter affecting non-irrigated crop areas for Rangpur, Faridpur and Mymensingh. Water deficits and excess water are the greatest constraints for rain fed rice yields in this region. The daily rainfall data for 30 years during the period 1981-2010 of the station Rangpur, Faridpur and Mymensingh districts are considered in this study. This study also considered weekly rainfall for 5 mm and 10 mm. The daily data were reduced in the weekly form and the drought index has been calculated using the probability of Markov chain model and goodness of fit using chi-square test. Drought is temporary but complex feature of the climate system. Agriculture drought is mainly concerned with inadequacy of rainfall. Markov chain model have been used to evaluate probabilities of getting a sequence of wet-dry weeks over this region. An index best on the parameters of this model has been suggested for agriculture drought measurement in this region. The results indicate that the Rangpur, Faridpur and Mymensingh districts are as follows: For Drought Index of Rainfall 5 mm and 10 mm in Rangpur District: the results indicate that the Rangpur region were found the mild drought in Annual, the occasionally drought in pre-kharif and kharif season, and the chronic drought Proneness in Rabi season. For Drought Index Rainfall 5 mm and 10 mm in Faridpur District: the Faridpur region were found the occasionally drought in Annual, pre-kharif and kharif season, and the chronic drought Proneness in Rabi season. For Drought Index Rainfall 5 mm and 10 mm in Mymensingh District: the results indicate that the region were found the mild drought in Annual, the occasionally drought in pre-kharif and kharif season, and the chronic drought Proneness in Rabi season. This study will be constructive to agricultural planners and irrigation engineers to identifying there as where agricultural development should be focused as a long –term drought improvement strategy. The level of drought proneness helps the early detection of agricultural drought and the crop production that is useful for talking timely release and remedy measures and other decisions by several organization of Bangladesh. It will also contribute toward a better understanding of the climatology of drought in major monsoon region of the world.
Changing Pattern of Fertility in Bangladesh
(University of Rajshahi, 2013) Jobbar, Md. Abdul; Islam, Md. Nurul
In this study, an attempt has been made to assess the factors associated with changing pattern of fertility in Bangladesh using nationally representative data from Bangladesh Demographic and Health Survey (BOHS), 2007. Multivariate technique named Logistic regression analysis has been used to find out the effects of the selected demographic and socio-economic factors on fertility pattern. Geometric distribution, Beta Geometric distribution and also multivariate technique named Cox's proportional hazard regression analysis have been used to identify the relationship between fertility, conception wait and fecundability. Fertility is still high in Bangladesh, though it has been declining over time. A major cause of declining fertility has been the steady increase in contraceptive use over the last 32 years; another major cause of declining fertility has been the steady increase the age at marriage. Current contraceptive prevalence rate (CPR) is 56% in 2007 BOHS (Mitra et, al., May 2009). The result of Logistic regression analysis shows that several socio-economic and demographic factors significantly affect on fertility. These are age at first marriage, current age of respondent, place of residence, religion, region, respondent's educational level, partner's educational level, work status of women, partner's occupation, contraceptive use, spousal age difference, marital duration, wealth index, body mass index, mass media contact, partner's age etc. From the result of logistic regression analysis, we observed that lower age at marriage giving higher fertility on the other hand higher educated women giving lower fertility. From place of residence we observed that fertility is higher in rural areas. There are several reasons, these include may be the rural women are less educated than urban women; rural women have less media connection etc. Regional difference reveals that fertility is higher in Rajshahi and lower in Sylhet Division. Barisal, Chittagong, Dhaka and Khulna division have intermediate levels of fertility. Religion has affect on fertility behavior through Muslims and Non-Muslims. The analysis shows that fertility among Muslims is higher as compared with Non-Muslims in each age group. Work status of women suggests that labor force participation may be consequence of lower fertility than non-working counterpart. Women who are involved with any service are not dependent on men (husbands), both socially and mentally have their own rights and absence of dependence, men cannot forcibly use women to increase their fertility. This has resulted in lower fertility. Fecundability is regarded as one of the important proximate parameters of fertility performance of the married women. Due to the complex nature of fecundability, we have attempted in this study to estimate mean fecundability from the first conception interval, which is not associated with postpartum infecundability. The first conception intervals have been estimated indirectly by utilizing the data. Since the cohort of women is not homogenous in regards to reproductive performance, we have attempted to estimate the mean recognizable effective fecundability by fitting the Pearson Type-I beta geometric model with parameters a and b to the observed distribution of first conception delay in addition to geometric distribution. In our analysis, we have estimated the parameters by the method of moments. The purpose of the present study, to estimate the mean conception delay, mean and corresponding variance of fecundability and levels, trends and differentials of fecundability of the Bangladeshi women. The mean conception delay of the Bangladeshi women has been found 23.88 months after their first marriage and the mean fecundability is 0.042, which is estimated by geometric distribution. The theoretical arithmetic and harmonic mean fecundabilities are found 0.045 and 0.042 respectively by fitting Beta geometric distribution. This study reveals that the women with higher education have lower mean conception delay and higher mean fecundability. We have also seen from this study that age at first marriage has negative relation with conception wait and positive relation with fecundabihity. It is observed that conception wait is decreasing and level of fecundability is increasing with the increasing age at first marriage whatever be the marital duration. Moreover, the fecundability decreases with the increasing marital duration whatever be the ages at first marriage. This indicates that the more the age at first marriage the higher the fecundability level and less the conception wait and vice-versa. Furthermore, the more the marital duration the less the fecundability and higher the conception wait and vice-versa. We get the significant regression coefficient between age at first marriage and conception wait as -1.849, which reflects that with the increase o 1.85 months. The trend analysis shows that conception wait is lower consequently fecundability is higher in the recent past than at some distant point of time. The multivariate analysis through the Cox's proportional Hazard Regression model shows that the respondent age at first marriage, current age of respondent, place of residence, religion, region, respondent's educational level, partner's educational level, work status of women, partner's occupation, contraceptive use, spousal age difference, marital duration, wealth index, body mass index, mass media contact and partner's age are found to have statistically significant association with the marriage to first conception wait. From the result of multivariate analysis we conclude that the associated factors which affect fertility those factors also affect fecundability with the same direction. f age at first marriage by one year, conception wait tends to decrease By 1.85 months. The trend analysis shows that conception wait is lower consequently fecundability is higher in the recent past than at some distant point of time. The multivariate analysis through the Cox's proportional Hazard Regression model shows that the respondent age at first marriage, current age of respondent, place of residence, religion, region, respondent's educational level, partner's educational level, work status of women, partner's occupation, contraceptive use, spousal age difference, marital duration, wealth index, body mass index, mass media contact and partner's age are found to have statistically significant association with the marriage to first conception wait.
Measuring the Level of Knowledge and Awareness of Tobacco Use in Bangladesh
(University of Rajshahi, 2016) Rahman, Md. Tahidur; Roy, Dulal Chandra; Sultana, Papia
Tobacco is identified as leading modifiable global disease risk factor. Bangladesh is one of the largest tobacco consuming countries in the world. The use of tobacco is more prevalent among male population in Bangladesh. Also the use of tobacco is increasing. Therefore the objective of this study is to measure the level of knowledge and awareness of the health consequences of smoking among Bangladeshi adults and its associates. We have used secondary data of size 9629 (Male=4468 and Female=5161) aged 15 years and above collected by the Global Adult Tobacco Survey (GATS), 2010. Binary logistic regression model has been used to identify significant correlates of knowledge and awareness of tobacco use in Bangladesh along with descriptive and bivariate analysis. Knowledge of health consequences of tobacco smoking, smokeless tobacco user and exposure to secondhand smoke (SHS) has been analyzed. According to their knowledge, the most common health consequences of tobacco smoking are serious illness 96.61%, lung cancer 94.24%, strokes 85.88% and heart attacks 88.43%. On the other hand, among the smokeless tobacco user 91.05% belief that smokeless tobacco use causes serious illness, 81.68% belief that smokeless tobacco use causes lunch cancer, 97.60% belief it causes stroke, and 71.42% belief it causes heart attack. Among the secondhand smoker 97.60% belief that it causes serious illness. Non- smokeless tobacco user has an equal knowledge on health risks than smokeless tobacco user OR= 1.00 but higher knowledge is found among secondhand smoker OR= 1.57. Current tobacco smoker is less knowledgeable than non-tobacco smoker OR= 0.57 which is statistically significant. For all kind of tobacco use it has been found that educated respondents are more knowledgeable than less educated people. The odds ratios imply that respondent of low wealth index are more likely to be knowledgeable than the respondent of lowest wealth index. Some of awareness policies have been analysed. We have found that tobacco users are more inspired by the marketing policy to use tobacco in the last 30 days than their counter parts. Rural respondents are more inspired to smoking tobacco than urban respondents. Female respondents are less inspired to smoking tobacco than male respondents and they are statistically significant. For tobacco smoking it has been found that educated respondents are more encouraged by the marketing policy to smoking tobacco than less educated people. We have also found that business man (small, large), farmer (land owner & farmer), agricultural /industrial worker/ daily laborer/other self- employed, homemaker /housework and student/other are more inspired by the marketing policy to smoking tobacco than those respondents are employers (Government, Non-Government). The odds ratios imply that respondents of low, middle and high wealth index are more inspired by the marketing policy to tobacco smoking than the respondents of lowest wealth index. For secondhand smoke, we have found that smoking is more allowed at home and job place for respondents who affected by secondhand smoking than their counter part and they are statistically significant. Smoking is more allowed at home and job place for rural respondents than urban respondents and they are statistically significant. Based on educational level it has been found that smoking is less allowed for higher educated respondents at home and job place than less educated respondents and they are statistically significant. We have also found that smoking are more allowed at home and job place for business man (small, large), farmer (land owner & farmer), agricultural /industrial worker/ daily laborer/other self- employed and retired and unemployed (able to work/unable to work) than employers (Government, Non-Government). It has been also found that smoking are less allowed for respondents of low, middle and higher wealth index at home and job place than respondents of lowest wealth index.
Association between Size at Birth and Maternal Factors in Rural Bangladesh: A Multivariate Approach
(University of Rajshahi, 2016) Kabir, A.Y.M. Alamgir; Qadri, Firdausi
In this research we explored the potential of the multivariate methods, CCA and PLS regression in studying the relationship between two sets of variables in public health research. This research will help the public health researchers in choosing the appropriate statistical methods if they want to study multiple outcomes and multiple exposures simultaneously. Additionally, we intended to identify a surrogative measure of low birth weight (LBW) using ROC curve and 4 machine learning algorithms, decision tree, random forest, support vector machine and neural network. Both the canonical correlation analysis and the PLS regression analysis has several advantages over the univariate methods. However, CCA is just an exploratory method very similar to Pearson’s correlation. Although one variable set is often considered as predictor and the other as criterion, it does not imply causal relationship between the set of exposures and the set of outcomes. On the other hand, PLS regression can help in establishing causal relationship between exposures and the outcomes. So, the choice of CCA or PLS regression depends on the objective of the study. In addition, this study will provide a realistic predictive model of LBW for Rural Bangladesh. The LBW can be predicted with 4 other simpler-to-measure anthropometries, length and head, chest and arm circumferences without measuring their weights, at a greater accuracy with the advent of the information technology.
Comparison of Performances of Machine Learning Techniques in Healthcare Data
(University of Rajshahi, Rajshahi, 2021) Maniruzzaman, Md.; Rahman, Md. Jahanur
Due to the increasing prevalence of diabetes and cancer, it is an urgent need to develop automated system that helps to detect disease using one of the modern technologies. Nowadays, Machine Learning (ML)-based methods have become very popular as an automatically model building techniques. Despite of the rapid development of theories for computational intelligence, application of ML-based classifiers to diabetes and cancer diagnosis remains a challenging issue. Still these ML-based classifiers did not give a satisfactory accuracy and therfore cannot correctly classify healthcare data like diabetes and cancer patients. Because most of the diabetes and cancer dataset are complex in nature and contains missing values, unusual observations, multi-collinearity problems and so on. In most of the existing research, the researcher did not use feature selection (FS) techniques to identify the risk factors of cancer and diabetes disease. They applied limited classifiers to classify and predict the diabetes and cancer status but they did not tune the hyper parameter of the classifiers, as a result, their accuracy and AUC were low. Thus, an attempt has been made in this study to increase the accuracy of the classifiers in diabetes and cancer data by considering the above factors in ML-based algorithm. The main objective of this study is to comparison the performances of ML-based methods in healthcare data and suggests the best model with better performance compared to the models published in the existing research.-----