Posterity and population growth: fertility intention among a cohort of Nigerian adolescents

Population growth is probably the greatest global challenge of the twenty-first century and fertility is a central element of this growth. Fertility is a human attribute which depends almost entirely on social, economic, political, cultural and psychological frameworks, making fertility intention an element of what individuals learn from a very young age as part of their socialisation into society. The fundamental significance of socio-psychological, environmental and cultural factors in what adolescents are assimilating on fertility cannot be exaggerated, yet, relevant information is limited. Eight factors deduced from ecological model and theory of planned behaviour were used to predict fertility intention among a cohort of Nigerian adolescents, using cross-sectional design. Mean fertility intention was 4.06 ± 1.34. Age and religion had no effect, but gender did. Self esteem, perceived parental expectation of fertility, attitude towards fertility and peer-related subjective norm are significant predictors. Media and ethnic attitude are insignificant predictors of, but are significantly related to fertility intention. Attitude towards a four-child family and perceived behavioural control yielded insignificant relationships with, and also failed to predict fertility intention. Perceived parental expectation of fertility, an interpersonal factor of the ecological model is the single most important predictor (β = 0.707, R² = 0.506, r = 0.711, and partial r = 0.710). Fertility intention points towards fertility decline, though sluggish and diminutive, thereby failing to reflect the need of Nigeria’s population pyramid to thin out from the base.

     

Emphasizing the experiences of researchers after RCR instructions: Introduction to Responsible Conduct of Research (RCR) in Malaysia

The purpose of this study is to highlight the experiences of individuals who participate in the Responsible Conduct of Research (RCR) training program held at various universities in Malaysia. In response to a mailing request sent to 40 individuals who had undertaken a RCR training program, 15 participants agreed to be interviewed. The results of the study showed that the three main reasons for participating in the training were as follows: anticipation for knowledge gained; personal experience with research misconduct; and establishing a new network of researchers. In terms of the positive effects gained from undertaking the training, the participants highlighted an increased awareness of the issues and problems related to research misconduct; the need to promote integrity in research conduct; a change in the way they conduct their research; and a change in the way they confront and address misconduct. The findings of this study should be valuable for policy makers and those involved in the management of research programs and ethics, as it demonstrated the importance of RCR training in equipping researchers with the necessary knowledge to conduct research responsibly, and to avoid research misconduct.     

Bayesian variable selection for the Cox regression model with missing covariates

In this paper, we develop Bayesian methodology and computational algorithms for variable subset selection in Cox proportional hazards models with missing covariate data. A new joint semi-conjugate prior for the piecewise exponential model is proposed in the presence of missing covariates and its properties are examined. The covariates are assumed to be missing at random (MAR). Under this new prior, a version of the Deviance Information Criterion (DIC) is proposed for Bayesian variable subset selection in the presence of missing covariates. Monte Carlo methods are developed for computing the DICs for all possible subset models in the model space. A Bone Marrow Transplant (BMT) dataset is used to illustrate the proposed methodology.     

Using econometric analysis of willingness-to-pay to investigate economic efficiency and equity of domestic water services in the West Bank

The paper is aimed at providing evidence on economic efficiency, and equity of distribution of domestic water services in the West Bank. The study utilizes the CVM as a means of monetizing public preferences and households’ WTP. In the CVM questionnaire, the dichotomous choice with follow-up debriefing questions format is followed by an open-ended follow-up question was undertaken. A second questionnaire survey was directed to employees from water institutions, which was mainly designed to investigate the reasons behind the full absence of private sector in the provision of water supply. The two samples were selected to ensure a representative samples in accordance with the Palestinian case. The main findings of this paper gauged the WTP with key socioeconomic variables suggested by economic theory and previous CVM studies. These results provide information on economic efficiency and equity of water distribution. The results will allow decision makers to develop new policies that can achieve more efficient and equitable domestic water services.     

Reviewing building construction statistics in Turkey: Stakeholders’ perspective

Construction is one of the industries of strategic economic importance. Governments using their national institutions are involved in the collection of economic statistics, which indicate the state of their economy in the form of an annual time series. However, the completeness and accuracy of these statistics is frequently questioned by the stakeholders within the sector. Therefore there is an increasing need for accurate, manageable and reliable statistics to enable sound analysis of the construction sector. The main purpose of this research is to review building construction statistics in Turkey. The objectives of the review are to 1) engage with users to ascertain their views on the statistics and to identify their needs, and 2) investigate whether the statistics in their present form continue to meet user needs, and identify options for change. As part of the review, a user consultation exercise is carried out to identify whether user needs are met by the statistics, as well as to ascertain users’ views on the European Statistical System (ESS) key dimensions of the quality of the statistics. This review of building construction statistics will facilitate statistical information to be presented in a more comprehensive manner, with sufficient detail, highly reliable in terms of quality and responsive to dynamic changes of the sector (such as inflation and structural adjustment policies).     

Deprivation: Endowment and Discrimination?

Social Indicators Research - Due to the lack of good-quality data, there has been no sound research about the economic welfare of the Romani in the countries where they live. Drawing on a...     

Estimation of the population mean and median using truncation-based ranked set samples

In this paper, a new sampling method is suggested, namely truncation-based ranked set samples (TBRSS) for estimating the population mean and median. The suggested method is compared with the simple random sampling (SRS), ranked set sampling (RSS), extreme ranked set sampling (ERSS) and median-ranked set sampling (MRSS) methods. It is shown that for estimating the population mean when the underlying distribution is symmetric, TBRSS estimator is unbiased and it is more efficient than the SRS estimator based on the same number of measured units. For asymmetric distributions considered in this study, TBRSS estimator is more efficient than the SRS for all considered distributions except for exponential distribution when the selection coefficient gets large. When compared with ERSS and MRSS methods, TBRSS performs well with respect to ERSS for all considered distributions except for U(0, 1) distribution, while TBRSS efficiency is higher than that of MRSS for U(0, 1) distribution. For estimating the population median, the TBRSS estimators have higher efficiencies when compared with SRS and ERSS. A real data set is used to illustrate the suggested method.     

Best linear unbiased and invariant estimation in location-scale families based on double-ranked set sampling

Abstract

In this article, we propose the best linear unbiased estimators (BLUEs) and best linear invariant estimators (BLIEs) for the unknown parameters of location-scale family of distributions based on double-ranked set sampling (DRSS) using perfect and imperfect rankings. These estimators are then compared with the BLUEs and BLIEs based on ranked set sampling (RSS). It is shown that under perfect ranking, the proposed estimators are uniformly better than the BLUEs and BLIEs obtained via RSS. We also propose the best linear unbiased quantile (BLUQ) and the best linear invariant quantile (BLIQ) estimators for normal distribution under DRSS. It is observed that the proposed quantile estimators are more efficient than the BLUQ and BLIQ estimators based on RSS for both perfect and imperfect orderings.     

Humerical. Results concerning the mle of an exponential parameter used in life testing

It was previously shown that the maximum likelihood estimator 0 of the scale parameter of the exponential distribution is asymptotically normal for type-I censoring. Applicability of the asymptotic normality results for finite samples is studied here by computer simulation for several different normalizing factors and for various levels of censoring. The use of the asymptotic results in statistical problems is illustrated by an example