This study considers data from 5 waves of the English Longitudinal Study of Ageing (ELSA). We aim to study the impact of demographic and self-rated health variables including disability and diseases on the survival of the population aged 50+. The disability variables that we consider are mobility impairment, difficulties in performing Activities of Daily Living (ADL) and Instrumental Activities of Daily Living (IADL). One of the problems with the survey study is missing observations. This may happen due to different reasons, such as errors, nonresponse and temporary withdrawals. We address this problem by applying single and multiple imputation methods. We then fit a Generalized Linear model (GLM) and Generalized Linear Mixed model (GLMM) to our data and show that a GLMM performs better than a GLM in terms of information criteria. We also look at the predictability of our models in terms of the time-dependent receiver operating characteristic (ROC) and the area of ROC, i.e. AUC. We conclude that among the disability factors, IADL and among the diseases, cancer significantly affect the survival of the English population aged 50 and older.

Decades of ambidexterity research have gained huge scholarly attention from diverse research areas like marketing, organizational learning, innovation management, supply chain management, strategy, and entrepreneurship. However, it has been observed that past studies do not provide a quantitative assessment of ambidexterity determinants applicable to small and medium firms. In response, this study attempts to address this gap by providing an extensive list of eight determinants that are significantly related to Small and Medium Enterprise (SME) ambidexterity. We employed Random effects meta-analytical procedure to examine the combined effect sizes of each determinant. The analysis was based on 37 empirical publications from 2004 to 2021, involving 8422 SME observations and 48 correlations. The findings of the meta-analysis revealed that all the considered determinants such as Knowledge management, Entrepreneurial orientation, Formalization, Market orientation, Networking, Technological capability, Organization context, and Environmental dynamism are heterogeneous, and they all exert a significant positive impact on ambidexterity.

Using state-level data from the Behavioral Risk Factor Surveillance System, we investigate the effects of household food-away-from-home and food-at-home expenditures on overweight rates, obesity rates, and combined rates. Our random effects model estimates suggest that food-away-from-home expenditures are positively related to obesity and combined rates, while food-at-home expenditures are negatively related to obesity and combined rates. However, the magnitudes of these effects, while statistically significant, are relatively small. Both food-at-home and food-away-from-home expenditures do not significantly influence overweight rates.

The sea cucumber fishery has been providing an important means of livelihood to the coastal fishing communities in Sri Lanka for centuries. Stock status, level of exploitation and mortality parameters of eleven commercial sea cucumber species were studied off the north-west and the east coasts of Sri Lanka using data collected from an underwater visual census and fishery-dependent surveys carried out in 2008 and 2009. The total abundance of sea cucumbers was higher in the north-west than the east (P < 0.01). However, the total abundance of all the species declined between 2008 and 2009. The commercial fishery predominantly relies on two nocturnal species: Holothuria spinifera and Thelenota anax. Holothuria spinifera had the highest contribution (73.2%) to the total landings in the north-west while this was provided by T. anax (93%) in the east. Both catch per unit effort and total landings declined in 2009 compared to 2008 having three exceptions (H. spinifera, Holothuria atra and Stichopus chloronotus) in the north-west. Further, the collection of immature individuals, reduced landings of high-value species and temporal shifting of fishing activities were observed in both areas. Two approaches (simple linear regression and random effects models) were used to estimate the natural mortality of sea cucumbers and the estimated values were 0.50 yr−1 and 0.45 yr−1, respectively. Apart from the management of local sea cucumber resources, this information is important to update the regional and global sea cucumber statistics as well as for launching regional management programmes.

We derive some decision rules to select best predictive regression models in a credibility context, that is, in a “random effects’ linear regression model with replicates. In contrast to usual model selection techniques on a collective level, our proposal allows to detect individual structures, even if they disappear in the collective.

We give exact, non-asymptotic results for the expected squared error loss for a predictor based on credibility estimation in different models. This involves correct accounting of random model parameters and the study of expected loss for shrinkage estimation. We support the theoretical properties of the new model selectors by a small simulation experiment.