NLCHECK: Stata module to check linearity assumption after model estimation

nlcheck is a simple diagnostic tool that can be used after fitting a model to quickly check the linearity assumption for a given predictor. nlcheck categorizes the predictor into bins, refits the model including dummy variables for the bins, and then performs a joint Wald test for the added parameters. Alternative, nlcheck uses linear splines for the adaptive model. Support for discrete variables is also provided. Optionally, nlcheck also displays a graph of the adjusted linear predictions from the original model and the adaptive model

Null Check Analysis

Null dereferencing is one of the most frequent bugs in Java systems causing programs to crash due to the uncaught NullPointerException. Developers often fix this bug by introducing a guard (i.e., null check) on the potentially-null objects before using them. In this paper we investigate the null checks in 717 open-source Java systems to understand when and why developers introduce null checks. We find that 35 of the if-statements are null checks. A deeper investigation shows that 71 of the checked-for-null objects are returned from method calls. This indicates that null checks have a serious impact on performance and that developers introduce null checks when they use methods that return null.

The influence of parent's body mass index on peer selection: An experimental approach using virtual reality

Relatively little is known about the influence of psychosocial factors, such as familial role modeling and social network on the development and maintenance of childhood obesity. We investigated peer se- lection using an immersive virtual reality environment. In a virtual schoolyard, children were confronted with normal weight and overweight avatars either eating or playing. Fifty-seven children aged 7–13 participated. Interpersonal distance to the avatars, child's BMI, self-perception, eating behavior and parental BMI were assessed. Parental BMI was the strongest predictor for the children's minimal distance to the avatars. Specifically, a higher mothers' BMI was associated with greater interpersonal distance and children approached closer to overweight eating avatars. A higher father's BMI was associated with a lower interpersonal distance to the avatars. These children approached normal weight playing and overweight eating avatar peers closest. The importance of parental BMI for the child's social approach/ avoidance behavior can be explained through social modeling mechanisms. Differential effects of pa- ternal and maternal BMI might be due to gender specific beauty ideals. Interventions to promote social interaction with peer groups could foster weight stabilization or weight loss in children.