Homelessness and Mental Disorder: Policy Considerations

Abstract

‘Photovoice’ is a photographic method that is used for several purposes (e.g. storytelling, building awareness, enhancing personal discovery), including conducting community-based participatory research (CBPR). Since its creation, photovoice has been used as a method for implementing health-related CBPR projects with people experiencing homelessness. As such, this article presents an overview of seven peer-reviewed publications regarding photovoice projects that were conducted with participants who are homeless. The goal of the review is to provide health professionals with a practical summary of the lessons learned from each photovoice project's methods and findings. Based on the literature, the review's major suggestion is that health professionals should plan and implement future projects according to the fundamental aspects of photovoice (e.g. empowerment of participants to document their community, facilitation of group discussions of photos, concerted efforts to reach policymakers).     

Memories pierce the heart: homoeroticism, Bollywood-style

In this essay, I enjoy using Amitabh Bachchan, perennial idol of the Bollywood screen, as a point of departure for ruminations on the construction of male friendship and male love within both Indian cinema and its primarily male audience (which, in a sense, represents in turn Hindi culture at large). Using translations of songs from Amitabh's films interlaced with my own personal experiences, we see how homosexuality thrives in covert yet recognized places in Indian culture, and how subtler forms of homosexuality are actually engendered under the auspices of normative patriarchal culture. Songs were translated by the author in collaboration with Jia Das.     

Identification and Inference With Many Invalid Instruments

We study estimation and inference in settings where the interest is in the effect of a potentially endogenous regressor on some outcome. To address the endogeneity, we exploit the presence of additional variables. Like conventional instrumental variables, these variables are correlated with the endogenous regressor. However, unlike conventional instrumental variables, they also have direct effects on the outcome, and thus are “invalid” instruments. Our novel identifying assumption is that the direct effects of these invalid instruments are uncorrelated with the effects of the instruments on the endogenous regressor. We show that in this case the limited-information-maximum-likelihood (liml) estimator is no longer consistent, but that a modification of the bias-corrected two-stage-least-square (tsls) estimator is consistent. We also show that conventional tests for over-identifying restrictions, adapted to the many instruments setting, can be used to test for the presence of these direct effects. We recommend that empirical researchers carry out such tests and compare estimates based on liml and the modified version of bias-corrected tsls. We illustrate in the context of two applications that such practice can be illuminating, and that our novel identifying assumption has substantive empirical content.     

Estimation and prediction of Marshall–Olkin extended exponential distribution under progressively type-II censored data

In this paper, we consider Marshall–Olkin extended exponential (MOEE) distribution which is capable of modelling various shapes of failure rates and aging criteria. The purpose of this paper is three fold. First, we derive the maximum likelihood estimators of the unknown parameters and the observed the Fisher information matrix from progressively type-II censored data. Next, the Bayes estimates are evaluated by applying Lindley’s approximation method and Markov Chain Monte Carlo method under the squared error loss function. We have performed a simulation study in order to compare the proposed Bayes estimators with the maximum likelihood estimators. We also compute 95% asymptotic confidence interval and symmetric credible interval along with the coverage probability. Third, we consider one-sample and two-sample prediction problems based on the observed sample and provide appropriate predictive intervals under classical as well as Bayesian framework. Finally, we analyse a real data set to illustrate the results derived.     

Bounds on Elasticities With Optimization Frictions: A Synthesis of Micro and Macro Evidence on Labor Supply

How can price elasticities be identified when agents face optimization frictions such as adjustment costs or inattention? I derive bounds on structural price elasticities that are a function of the observed effect of a price change on demand, the size of the price change, and the degree of frictions. The degree of frictions is measured by the utility losses agents tolerate to deviate from the frictionless optimum. The bounds imply that frictions affect intensive margin elasticities much more than extensive margin elasticities. I apply these bounds to the literature on labor supply. The utility costs of ignoring the tax changes used to identify intensive margin labor supply elasticities are typically less than 1% of earnings. As a result, small frictions can explain the differences between micro and macro elasticities, extensive and intensive margin elasticities, and other disparate findings. Pooling estimates from existing studies, I estimate a Hicksian labor supply elasticity of 0.33 on the intensive margin and 0.25 on the extensive margin after accounting for frictions.     

On progressively censored inverted exponentiated Rayleigh distribution

In this paper, we discuss a progressively censored inverted exponentiated Rayleigh distribution. Estimation of unknown parameters is considered under progressive censoring using maximum likelihood and Bayesian approaches. Bayes estimators of unknown parameters are derived with respect to different symmetric and asymmetric loss functions using gamma prior distributions. An importance sampling procedure is taken into consideration for deriving these estimates. Further highest posterior density intervals for unknown parameters are constructed and for comparison purposes bootstrap intervals are also obtained. Prediction of future observations is studied in one- and two-sample situations from classical and Bayesian viewpoint. We further establish optimum censoring schemes using Bayesian approach. Finally, we conduct a simulation study to compare the performance of proposed methods and analyse two real data sets for illustration purposes.     

Sampling designs for landsat crop surveys

The problem of designing large scale crop surveys which utilize Landsat data is addressed in this paper. Emphasis is on stratification and sampling approaches designed to achieve preselected precisions while permitting manageable data processing and survey costs. A dynamic area sampling frame which is versatile and highly suited for sampling of Landsat data is discussed along with the use of rotation sampling for incorporating multiple years of information into the area estimation     

Substance use during sexual and physical assault in HIV-infected persons

Data from the HIV-Alcohol Longitudinal Cohort was used to determine the prevalence of substance use by victims and assailants during physical and sexual assault against HIV-infected persons and whether these findings differed by gender. Of the sexually assaulted participants, 31% of victims and 70% of assailant(s) had used drugs/alcohol during sexual assault. Compared with men, women had higher odds of substance use during sexual assault (adjusted odds ratio [OR] 3.8, 95% confidence interval [CI] 1.6 to 8.7) and of substance use by their assailant(s) during sexual assault (adjusted OR 5.9, 95% CI 1.7 to 20.6) in adjusted analysis. Of the physically assaulted participants, 66% of victims and 85% of assailants used drugs/alcohol during physical assault; these results did not differ by gender.