Geo-sampling in developing nations

RTI International created a geospatial grid-based sampling methodology that: achieved a probability-based household sample and unbiased estimates; was comparable across countries; used simple frame data available from the in-country census; and was efficient with minimal training to local field staff. The methodology used 1 km² LandScan world population data, which was further subdivided to smaller grid cells ranging from 50 to 150 m². To guide fieldwork, georeferenced maps were generated and viewed without an Internet connection using a third-party app and the tablet’s internal global positioning systems receiver. The field staff’s location was displayed in real time as a blue dot enabling field staff to determine household inclusivity. This methodology was successfully implemented for household surveys Latin America, Africa, and Asia. The design is transferable, adaptable, scalable, and can be used anywhere in the world.     

Can better parenting be achieved through short prevention programs? The challenge of universal prevention through Strengthening Families Program 11–14

With the increase in substance use by young people in recent years' there has been a growth in evidence‐based programs aimed at preventing this problem. This study aims to assess possible changes in family and parental dynamics among families taking part in a short (6‐session) universal program. These changes might act as protective factors for families in preventing substance use. A quasi‐experimental design was used' with pretest and posttest evaluations. The participating schools meeting the inclusion criteria were randomly assigned to the experimental or control group. The sample was made up of 16 experimental groups and 17 control groups' with the participation of 353 parents and 289 youths. The results confirm the strengthening of the families by improving the following key components of parenting: resilience' involvement' family conflicts' and positive parenting. Reinforcing parenting skills through a short program is a good strategy to take' ensuring high levels of adherence (86.40% retention of the initial sample). Hence future universal prevention programs must not just set their sights on high levels of effectiveness' but also on efficiency.     

Modification of Semivalues for Games with Coalition Structures

Consideration of reference systems for semivalues leads us to a global representation of the action of a semivalue on a game. Using this representation, we show how to modify semivalues to take account of coalition structures on the player set. The players' allocations according to a semivalue, including a modified semivalue, can be computed by means of products of matrices obtained from the multilinear extension of the game.     

Strength in Process: Using Concept Mapping to Inform Community Coalition Development

This study reports on the use of Concept Mapping to delineate a conceptual framework germane to the planning and initial formation of tri-county rural diabetes coalition in a southeast US community. The focus of the tricounty coalition is to reduce diabetes-related inequalities in vulnerable populations. After a review of pertinent literature on community coalitions, this article explicates Concept Mapping processes utilized to plan and organize the formation of a coalition, offers analyses of the results, and discusses implications for current and future practices pertaining to community coalition work.     

Performance of spare parts supply chains in developing industries

Spare parts supply chains of manufacturing equipment in developing industries such as the Saudi manufacturing sector often operate in one direction. Importing production machinery and setups to run such developing industries, from more developed industrial countries, sway the flow of spare supplies upstream. Based on empirical data collected from 210 local manufacturing firms, this study characterises and models such supply chains. The effects of supplier proximity, diversity and time lag on spare parts supply chain performance were explained using structural equation modelling. Delivery time lag and supplier diversity increased the deficiency of spare parts availability. Opposite to earlier consensus found in the literature, the impact of supplier proximity on spare parts supply chain performance was insignificant. Recent improvements in the agility and capacity of logistical services might have diminished the influence of supplier remoteness. However, supplier proximity correlated with supplier diversity in such supply chains.     

Mixed ranked set sampling design

The main focus of agricultural, ecological and environmental studies is to develop well designed, cost-effective and efficient sampling designs. Ranked set sampling (RSS) is one method that leads to accomplish such objectives by incorporating expert knowledge to its advantage. In this paper, we propose an efficient sampling scheme, named mixed RSS (MxRSS), for estimation of the population mean and median. The MxRSS scheme is a suitable mixture of both simple random sampling (SRS) and RSS schemes. The MxRSS scheme provides an unbiased estimator of the population mean, and its variance is always less than the variance of sample mean based on SRS. For both symmetric and asymmetric populations, the mean and median estimators based on SRS, partial RSS (PRSS) and MxRSS schemes are compared. It turns out that the mean and median estimates under MxRSS scheme are more precise than those based on SRS scheme. Moreover, when estimating the mean of symmetric and some asymmetric populations, the mean estimates under MxRSS scheme are found to be more efficient than the mean estimates with PRSS scheme. An application to real data is also provided to illustrate the implementation of the proposed sampling scheme.     

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.