Modified Ridge Parameters for Seemingly Unrelated Regression Model

In this paper, we modify a number of new biased estimators of seemingly unrelated regression (SUR) parameters which are developed by Alkhamisi and Shukur (2008), AS, when the explanatory variables are affected by multicollinearity. Nine ridge parameters have been modified and compared in terms of the trace mean squared error (TMSE) and (PR) criterion. The results from this extended study are the also compared with those founded by AS. A simulation study has been conducted to compare the performance of the modified ridge parameters. The results showed that under certain conditions the performance of the multivariate ridge regression estimators based on SUR ridge RMSmax is superior to other estimators in terms of TMSE and PR criterion. In large samples and when the collinearity between the explanatory variables is not high the unbiased SUR, estimator produces a smaller TMSEs.Multicollinearity; modified SUR ridge regression; Monte Carlo simulations; TMSE

Associations between psychosocial wellbeing and experience of gender-based violence at community, household, and intimate-partner levels among a cross-sectional cohort of young people living with and without HIV during COVID-19 in Cape Town, South Africa

Background Growing evidence indicates that gender-based violence (GBV) increased during COVID-19. We investigated self-reported impact of the pandemic on GBV at community, household and intimate partner (IPV) levels among young people and its associations with psychosocial wellbeing, i.e., COVID-related stressors and mental health. Methods Cross-sectional data were drawn from a survey with young people ages 13–24 (N = 536) living with HIV (YPLWH) and without HIV (YPLWoH), in peri-urban Cape Town, South Africa. The survey, conducted February-October 2021, examined the impact of the initial lockdown on experience and perceived changes in GBV at each level, and pandemic-related psychosocial wellbeing. Descriptive statistics and binomial and multinomial regression analyses were conducted to illustrate exposure and perceived changes in GBV since lockdown, and their association with COVID-related stress factors (e.g., social isolation, anxiety about COVID), mental health (e.g., depression, anxiety), and other risk factors (e.g., age, gender, socioeconomic status) by HIV status. Results Participants were 70% women with mean age 19 years; 40% were living with HIV. Since lockdown, YPLWoH were significantly more likely than YPLWH to perceive community violence as increasing (45% vs. 28%, p < 0.001), and to report household violence (37% vs. 23%, p = 0.006) and perceive it as increasing (56% vs. 27%, p = 0.002) (ref: decreasing violence). YPLWoH were also more likely to report IPV experience (19% vs. 15%, p = 0.41) and perception of IPV increasing (15% vs. 8%, p = 0.92). In adjusted models, COVID-related stressors and common mental health disorders were only associated with household violence. However, indicators of economic status such as living in informal housing (RRR = 2.07; 95% CI = 1.12–3.83) and food insecurity (Community violence: RRR = 1.79; 95% CI = 1.00-3.20; Household violence: RRR = 1.72; 95% CI = 1.15–2.60) emerged as significant risk factors for exposure to increased GBV particularly among YPLWoH. Conclusions Findings suggest that for young people in this setting, GBV at community and household levels was more prevalent during COVID-19 compared to IPV, especially for YPLWoH. While we found limited associations between COVID-related stressors and GBV, the perceived increases in GBV since lockdown in a setting where GBV is endemic, and the association of household violence with mental health, is a concern for future pandemic responses and should be longitudinally assessed. Supplementary Information The online version contains supplementary material available at 10.1186/s12889-023-16945-5

Developing ridge estimation method for median regression

In this paper, the ridge estimation method is generalized to the median regression. Though the least absolute deviation (LAD) estimation method is robust in the presence of non-Gaussian or asymmetric error terms, it can still deteriorate into a severe multicollinearity problem when non-orthogonal explanatory variables are involved. The proposed method increases the efficiency of the LAD estimators by reducing the variance inflation and giving more room for the bias to get a smaller mean squared error of the LAD estimators. This paper includes an application of the new methodology and a simulation study as well

On Median and Ridge Estimation of SURE Models

This doctoral dissertation is a progressive generalization of some of the robust estimation methods in order to make those methods applicable to the estimation of the Seemingly Unrelated Regression Equations (SURE) models. The robust methods are each of the Least Absolute Deviations (LAD) estimation method, also known as the median regression, and the ridge estimation method. The first part of the dissertation consists of a brief explanation of the LAD and the ridge methods. The contribution of this investigation to the statistical methodology is focused on in the second part of the dissertation, which consists of 5 articles. The first article is a generalization of the median regression to the estimation of the SURE models. The proposed methodology is compared with each of the Generalized Least Squares (GLS) method and the median regression of individual regression equations. The second article generalizes the median regression on the conventional multivariate regression analysis, i.e., the SURE models with the same design matrices of the equations. The results are compared with the median regression of individual regression equations and the conventionally used OLS estimation method for such models (which is equivalent to the GLS estimation, as well). In the third article, the author develops ridge estimation for the median regression. Some properties and the asymptotic distribution of the estimator presented are investigated, as well. An empirical example is used to assess the performance of the new methodology. In the fourth article, the properties of some biasing parameters used in the literature for ridge regression are investigated when they are used for the new methodology proposed in the third article. In the last article, the methodologies of the four preceding articles are assembled in a more generalized methodology to develop the ridge-type estimation of the LAD method for the SURE models. This article has also provided an opportunity to investigate the behavior of some biasing parameters for the SURE models, which were previously used by some researchers in a non-SURE context

Developing Median Regression for SURE Models - with Application to 3-Generation Immigrants’ data in Sweden

In this paper we generalize the median regression method in order to make it applicable to systems of regression equations. Given the existence of proper systemwise medians of the errors from different equations, we apply the weighted median regression with the weights obtained from the covariance matrix of errors from different equations calculated by conventional SURE method. The Seemingly Unrelated Median Regression Equations (SUMRE) method produces results that are more robust than the usual SURE or single equations OLS estimations when the distributions of the dependent variables are not symmetric. Moreover, the estimations of the SUMRE method are also more efficient than those of the cases of single equation median regressions when the cross equations errors are correlated. More precisely, the aim of our SUMRE method is to produce a harmony of existing skewness and correlations of errors in systems of regression equations. A theorem is derived and indicates that even with the lack of statistically significant correlations between the equations, using the SMRE method instead of the SURE method will not damage the estimation of parameters. A Monte Carlo experiment was conducted to investigate the properties of the SUMRE method in situations where the number of equations in the system, number of observations, strength of the correlations of cross equations errors and the departure from the normality distribution of the errors were varied. The results show that, when the cross equations correlations are medium or high and the level of skewness of the errors of the equations are also medium or high, the SUMRE method produces estimators that are more efficient and less biased than the ordinary SURE GLS estimators. Moreover, the estimates of applying the SUMRE method are also more efficient and less biased than the estimates obtained when applying the OLS or single equation median regressions. In addition, our results from an empirical application are in accordance with what we discovered from the simulation study, with respect to the relative gain in efficiency of SUMRE estimators compared to SURE estimators, in the presence of Skewness of error terms.Median regression; SURE models; robustness; efficiency

Parental support in promoting children’s health behaviours and preventing overweight and obesity – a long-term follow-up of the cluster-randomised healthy school start study II trial

Abstract Background Effects of obesity prevention interventions in early childhood are only meaningful if they are sustained over time, but long-term follow-up studies are rare. The school-based cluster-randomised Healthy School Start (HSS) trial aimed at child health promotion and obesity prevention through parental support was carried out in 31 pre-school classes (378 families) in disadvantaged areas in Sweden during 2012–2013. Post-intervention results showed intervention effects on intake of unhealthy foods and drinks, and lower BMI-sds in children with obesity at baseline. This study aimed to evaluate the long-term effectiveness 4 years post-intervention. Methods Data were collected from 215 children in March–June 2017. Child dietary intake, screen time, and physical activity were measured through parental-proxy questionnaires. Child height and weight were measured by the research group. Group effects were examined using Poisson, linear, logistic, and quantile regression for data on different levels. Analyses were done by intention to treat, per protocol, and sensitivity analyses using multiple imputation. Results No between-group effects on dietary intake, screen time, physical activity, or BMI-sds were found for the entire group at the four-year follow-up. In girls, a significant subgroup-effect was found favouring intervention compared to controls with a lower intake of unhealthy foods, but this was not sustained in the sensitivity analysis. In boys, a significant sub-group effect was found where the boys in the intervention group beyond the 95th percentile had significantly higher BMI-sds compared to boys in the control group. This effect was sustained in the sensitivity analysis. Analyses per protocol showed significant intervention effects regarding a lower intake of unhealthy foods and drinks in the children with a high intervention dose compared to controls. Conclusions Four years after the intervention, only sub-group effects were found, and it is unlikely that the HSS intervention had clinically meaningful effects on the children. These results suggest that school-based prevention programmes need to be extended for greater long-term effectiveness by e.g. integration into school routine practice. In addition, results showed that children with a high intervention dose had better long-term outcomes compared to controls, which emphasises the need for further work to increase family engagement in interventions. Trial registration ISRCTN, ISRCTN39690370, retrospectively registered March 1, 2013, http://www.isrctn.com/ISRCTN39690370

Cognitive social capital as a health-enabling factor for STI testing among young men in Stockholm, Sweden : A cross-sectional population-based study

Objective: To assess whether different forms of cognitive social capital increased the relative probability of testing for sexually transmitted infections (STIs) among young men living in Stockholm, Sweden. Methods: A population-based cross-sectional study was conducted in 2017 with men aged 20–29 years living in Stockholm County, Sweden (n = 523). The main outcome was STI testing patterns (never tested, tested only within a 12-month period, tested only beyond a 12-month period, repeatedly tested). The main exposure were two forms of cognitive social capital: social support (having received help, having someone to share inner feelings with) and institutionalized trust (in school, healthcare, media). Data were analyzed using weighted multivariable multinomial logistic regression to obtain adjusted weighted relative probability ratio (aRPR). Results: After adjusting for confounding factors, receiving help (aRPR: 5.2, 95% CI: 1.7–16.2) and having someone to share inner feelings with (aRPR: 3.1, 95% CI: 1.2–7.7) increased the relative probabilities of young men testing for STIs, but only for those testing beyond a 12-month period. Trust in media increased the relative probability of STI testing for those testing only within a 12-month period (aRPR: 2.6, 95% CI: 1.1–6.1) and for those testing repeatedly (aRPR: 3.6, 95% CI: 1.5–8.8). Conclusion: Young men in Stockholm County exhibit distinct STI testing patterns. Social support and trust in media were factors that increased the probability of being tested for STIs, with this effect varying according to the young men's STI testing pattern. Further studies are required to explore how trust in media might promote STI testing in this population