Robustness of Some Estimators of Linear Model with Autocorrelated Error Terms When Stochastic Regressors are Normally Distributed

Performances of estimators of the linear model under different level of autocorrelation (ρ) are known to be affected by different specifications of regressors. The robustness of some methods of parameter estimation of linear model to autocorrelation are examined when stochastic regressors are normally distributed. Monte Carlo experiments were conducted at both low and high replications. Comparison and preference of estimator(s) are based on their performances via bias, absolute bias, variance and more importantly the mean squared error of the estimated parameters of the model. Results show that the performances of the estimators improve with increased replication. In estimating all the parameters of the model, the Ordinary Least Square (OLS) estimator is more efficient than any of the Generalized Least Square (GLS) estimators considered when − 0.25 \u3c ρ ≤ 0.25; and the Maximum Likelihood (ML) and the Hildreth and LU (HILU) estimators are robust

Understanding Etiologies of Road Traffic Crashes, Injuries, and Death for Patients at National Hospital Abuja: A Qualitative Content Analysis Using Haddon’s Matrix

Road traffic crashes and sequelae are reaching pandemic proportions globally and have currently achieved disproportionately high levels in Nigeria. Quantitative studies are accumulating in the peer-reviewed literature, but there is a paucity of qualitative research in Nigeria. Data for this study of structural and behavioral factors of road traffic crashes and injuries in Federal Capital Territory were collected in semi-structured interviews with crash survivors at National Hospital Abuja. Interviews were analyzed via qualitative content analysis, revealing crash location and participant beliefs about crash etiologies. Units of analysis were developed from participant statements and were structured within four a priori etiologic categories using Haddon’s (1980) matrix: human-, vehicle-, physical environment-, and socioeconomic environment-related. Subcategories were generated. Human-related subcategories included reckless behavior and drivers, limited technical knowledge and skill. Vehicle-related subcategories included vehicular disrepair and lack of safety equipment. Physical environment-related subcategories included road disrepair, infrastructural inadequacy, and weather. Socioeconomic environment-related subcategories included government, prehospital care, money, and prayer. Subcategories were organized temporally by pre-event, event, and post-event phases, with most units of analysis allocated in the pre-event phase. These qualitative results can be utilized to guide future research along community-aligned priorities, and to structure community-engaged preventative and interventional efforts

Understanding Etiologies of Road Traffiffic Crashes, Injuries, and Death for Patients at National Hospital Abuja: A Qualitative Content Analysis Using Haddon\u27s Matrix

Road traffic crashes and sequelae are reaching pandemic proportions globally and have currently achieved disproportionately high levels in Nigeria. Quantitative studies are accumulating in the peer-reviewed literature, but there is a paucity of qualitative research in Nigeria. Data for this study of structural and behavioral factors of road traffic crashes and injuries in Federal Capital Territory were collected in semi-structured interviews with crash survivors at National Hospital Abuja. Interviews were analyzed via qualitative content analysis, revealing crash location and participant beliefs about crash etiologies. Units of analysis were developed from participant statements and were structured within four a priori etiologic categories using Haddon\u27s (1980) matrix: human-, vehicle-, physical environment-, and socioeconomic environment-related. Subcategories were generated. Human-related subcategories included reckless behavior and drivers, limited technical knowledge and skill. Vehicle-related subcategories included vehicular disrepair and lack of safety equipment. Physical environment-related subcategories included road disrepair, infrastructural inadequacy, and weather. Socioeconomic environment-related subcategories included government, prehospital care, money, and prayer. Subcategories were organized temporally by pre-event, event, and post-event phases, with most units of analysis allocated in the preevent phase. These qualitative results can be utilized to guide future research along community-aligned priorities, and to structure community-engaged preventative and interventional efforts

International Study of the Epidemiology of Paediatric Trauma : PAPSA Research Study

Objectives: Trauma is a significant cause of morbidity and mortality worldwide. The literature on paediatric trauma epidemiology in low- and middle-income countries (LMICs) is limited. This study aims to gather epidemiological data on paediatric trauma. Methods: This is a multicentre prospective cohort study of paediatric trauma admissions, over 1 month, from 15 paediatric surgery centres in 11 countries. Epidemiology, mechanism of injury, injuries sustained, management, morbidity and mortality data were recorded. Statistical analysis compared LMICs and high-income countries (HICs). Results: There were 1377 paediatric trauma admissions over 31 days; 1295 admissions across ten LMIC centres and 84 admissions across five HIC centres. Median number of admissions per centre was 15 in HICs and 43 in LMICs. Mean age was 7 years, and 62% were boys. Common mechanisms included road traffic accidents (41%), falls (41%) and interpersonal violence (11%). Frequent injuries were lacerations, fractures, head injuries and burns. Intra-abdominal and intra-thoracic injuries accounted for 3 and 2% of injuries. The mechanisms and injuries sustained differed significantly between HICs and LMICs. Median length of stay was 1 day and 19% required an operative intervention; this did not differ significantly between HICs and LMICs. No mortality and morbidity was reported from HICs. In LMICs, in-hospital morbidity was 4.0% and mortality was 0.8%. Conclusion: The spectrum of paediatric trauma varies significantly, with different injury mechanisms and patterns in LMICs. Healthcare structure, access to paediatric surgery and trauma prevention strategies may account for these differences. Trauma registries are needed in LMICs for future research and to inform local policy

Family planning desires of older adults (50 years and over) in Botswana

Background: This study analysed the views of a stratified sample of 444 older adult women from selected health districts in Botswana on their family planning (FP) use, knowledge, accessibility and availability.Methods: Four health districts (two rural and two urban) were purposively selected. The sample of 444 older adults was proportionally allocated to the districts. The snowball technique was used in identifying older adults from each district.Results: Contraceptive prevalence among the older adults is low (25. 2%); ever used rate was 23.6%, with unmet need as high as 75.2%. The traditional methods are mainly used. Knowledge, availability and accessibility of the natural methods are high. The likelihood ratio test shows that age, educational status, marital status and employment jointly significantly predicts (p 0.05) the use of FP.Conclusion: Family planning programme developers and policy-makers should develop educational interventions that will be age specific and relevant to older adults

Relationship between socio-economic characteristics of older adults’ women and family planning use in Botswana

Older adults (50 years and over) are still sexually active and therefore vulnerable to unplanned pregnancy, infection of STIs and HIV, yet there are no programmes in place to cater for their family planning needs. The objective of the study is to show how some socio-economic characteristics of older adults influence their family planning (FP) use. The study used a stratified random sampling design where four health districts (two urban and two rural) were purposively selected and the sample size of 444 older adult women allocated to the districts using proportional allocation to size. Snowball technique was used in identifying respondents. The multinomial logistic regression analysis reveals that while age, marital status, educational qualification, employment status, menopausal status, district and desire for another child jointly significantly predict FP use, only menopausal status and desire for another child individually significantly (p<0.01) predict FP use. Older adult women who desired another child were significantly (p<0.01) 7.5 times more likely to use family planning (FP) methods than those who do not want another child. The postmenopausal older adult women were less likely to use FP methods than those in their premenopausal state (OR = 0.13). Women with no schooling were less likely to use FP methods than those with degree/professional qualifications. Single and married women were less likely to use FP methods than the divorced/widowed/separated. The study recommends the promotion of education and training on FP use among the older adult women that will take into consideration their menopausal status and desire for another child. The training should be home-based

Performances of some estimators of linear model with autocorrelated error terms when regressors are normally distributed

Different specification of regressors and levels of autocorrelation are known to affect the performances of estimators of linear model with autocorrelated error terms. In this paper, we examined the performances of the ordinary least square (OLS) and four feasible generalized least estimators namely; Cochrane Orcut (CORC), Hidreth – Lu (HILU), Maximum Likelihood (ML), Maximum Likelihood Grid (MLGD) when regressors are normally distributed at various levels of autocorrelation and sample size through Monte – Carlo studies. The estimators are compared by examing the finite properties of estimators namely; sum of biases, sum of absolute biases, sum of variances and sum of the mean squared error of the estimated parameter of the model. Results show that when the autocorrelation level is small (&#961=0.4), the MLGD estimator is best except when the sample size is large (n=80) where the CORC estimator is best. When autocorrelation is high (&#961=0.8), the CORC estimator is best except when the sample size is small (n=80) where the ML estimator is best. When autocorrelation is very high (&#961=0.9), the HILU estimator is best except when the sample size is large where the CORC estimator is best. Furthermore, when the autocorrelation level tends to unity (&#961 &#8594 1), the HILU estimator is best in all the sample sizes. IJONAS Vol. 3 (1) 2007: pp.22-2

Spatial patterns and determinants of fertility levels among women of childbearing age in Nigeria

Background: Despite aggressive measures to control the population in Nigeria, the population of Nigeria still remains worrisome. Increased birth rates have significantly contributed to Nigeria being referred to as the most populous country in Africa. This study analyses spatial patterns and contributory factors to fertility levels in different states in Nigeria. Method: The 2013 Nigerian Demographic Health Survey (NDHS) data were used to investigate the determinants of fertility levels in Nigeria using the geo-additive model. The fertility levels were considered as count data. Negative Binomial distribution was used to handle overdispersion of the dependent variable. Spatial effects were used to identify the hotspots for high fertility levels. Inference was a fully Bayesian approach. Results were presented within 95% credible Interval (CI). Results: Secondary or higher level of education of the mother, Yoruba ethnicity, Christianity, family planning use, higher wealth index, previous Caesarean birth were all factors associated with lower fertility levels in Nigeria. Age at first birth, staying in rural place of residence, the number of daughters in a household, being gainfully employed, married and living with a partner, community and household effects contribute to the high fertility patterns in Nigeria. The hotspots for high fertility in Nigeria are Kano, Yobe, Benue, Edo and Bayelsa states. Conclusion: State-specific policies need to be developed to address fertility levels in Nigeria. (Full text of the research articles are available online at www.medpharm.tandfonline.com/ojfp) S Afr Fam Pract 2017; DOI: 10.1080/20786190.2017.129269

Spatial pattern and determinants of unmet need of family planning in Nigeria

Background: Nigeria still grapples with low family planning (FP) use and a high fertility rate. This study explores the factors associated with the unmet need for FP and the coldspots of unmet need for FP in Nigeria.Methods: The 2013 Nigerian Demographic Health Survey (NDHS) data was used to investigate the unmet need for FP in Nigeria. A geo-additive model was specified to simultaneously measure the fixed, nonlinear, spatial and random effects inherent in the data. The fixed effect of categorical covariates was modelled using the diffuse prior, the nonlinear effect of continuous variable was modelled using the P-spline with second-order random walk, the spatial effects followed Markov random field priors while the exchangeable normal priors were used for the random effect of the community. The binomial distribution was used to handle the dichotomous nature of the dependent variable.Results: North East (OR: 1.8404, CI: 1.6170, 2.0941), North West (OR: 1.1145, CI: 1.1454, 1.1789), primary education (OR: 1.0441, CI: 0.9680, 1.1286), Hausa (OR: 2.7031, CI: 2.3037, 3.1513), birth interval greater than 12 months (OR: 1.0909, CI: 1.0447, 1.1379), community (OR: 1.6733, CI: 1.5261, 1.7899) and states (OR: 6.0879, CI: 2.5995, 29.6274) significantly increased the unmet need for FP.Conclusion: The unmet need for FP in Nigeria is positively associated with the Northern region, low level of education and birth interval

Time Series Model for Predicting the Mean Death Rate of a Disease

This study develops a time series model to estimate the mean death rate of either an emerging disease or re-emerging disease with a bilinear induced model. The estimated death rate converges rapidly to the true parameter value for a given mean death at time t. The derived model could be used in predicting the m-step future death rate value of a given disease. We illustrated the new concept with real life data