influence.ME: tools for detecting influential data in mixed effects models

influence.ME provides tools for detecting influential data in mixed effects models. The application of these models has become common practice, but the development of diagnostic tools has lagged behind. influence.ME calculates standardized measures of influential data for the point estimates of generalized mixed effects models, such as DFBETAS, Cook’s distance, as well as percentile change and a test for changing levels of significance. influence.ME calculates these measures of influence while accounting for the nesting structure of the data. The package and measures of influential data\ud are introduced, a practical example is given, and strategies for dealing with influential data are suggested

Interviewer BMI effects on under- and over-reporting of restrained eating: evidence from a national Dutch face-to-face survey and a postal follow-up

Contains fulltext : 102650pub.pdf (publisher's version ) (Open Access)Objectives To determine the effect of interviewer BMI on self-reported restrained eating in a face-to-face survey and to examine under- and over-reporting using the face-to face study and a postal follow-up. Methods A sample of 1,212 Dutch adults was assigned to 98 interviewers with different BMI who administered an eating questionnaire. To further evaluate misreporting a mail follow-up was conducted among 504 participants. Data were analyzed using two-level hierarchical models. Results Interviewer BMI had a positive effect on restrained eating. Normal weight and pre-obese interviewers obtained valid responses, underweight interviewers stimulated underreporting whereas obese interviewers triggered overreporting. Conclusion In face-to-face interviews self-reported dietary restraint is distorted by interviewer BMI. This result has implications for public health surveys, the more so given the expanding obesity epidemic.5 p

The Hierarchical Age-Period-Cohort model: Why does it find the results that it finds?

It is claimed the hierarchical-age–period–cohort (HAPC) model solves the age–period–cohort (APC) identification problem. However, this is debateable; simulations show situations where the model produces incorrect results, countered by proponents of the model arguing those simulations are not relevant to real-life scenarios. This paper moves beyond questioning whether the HAPC model works, to why it produces the results it does. We argue HAPC estimates are the result not of the distinctive substantive APC processes occurring in the dataset, but are primarily an artefact of the data structure—that is, the way the data has been collected. Were the data collected differently, the results produced would be different. This is illustrated both with simulations and real data, the latter by taking a variety of samples from the National Health Interview Survey (NHIS) data used by Reither et al. (Soc Sci Med 69(10):1439–1448, 2009) in their HAPC study of obesity. When a sample based on a small range of cohorts is taken, such that the period range is much greater than the cohort range, the results produced are very different to those produced when cohort groups span a much wider range than periods, as is structurally the case with repeated cross-sectional data. The paper also addresses the latest defence of the HAPC model by its proponents (Reither et al. in Soc Sci Med 145:125–128, 2015a). The results lend further support to the view that the HAPC model is not able to accurately discern APC effects, and should be used with caution when there appear to be period or cohort near-linear trends

Religious socialisation and fertility: transition to third birth in the Netherlands

Although previous studies have demonstrated that religious people in Europe have larger families, the role played by religious socialisation in the context of contemporary fertility behaviour has not yet been analysed in detail. This contribution specifically looks at the interrelation between religious socialisation and current religiosity and their impact on the transition to the third child for Dutch women. It is based on data of the first wave of the Netherlands Kinship Panel Study (2002–2004) and uses event history analysis. The transitions to first, second and third birth are modelled jointly with a control for unobserved heterogeneity. The findings provide evidence for an impact of women’s current church attendance as well as religious socialisation measured by their fathers’ religious affiliation, when they were teenagers. A religious family background remains influential even when a woman has stopped attending church. The effects of religious indicators strengthen over cohorts. Moreover, the combined religious make-up of the respondent’s parents also significantly determines the progression to the third child.S’il est bien établi que les croyants en Europe ont plus d’enfants que les autres, le rôle de la socialisation religieuse dans le contexte de la fécondité contemporaine n’a pas encore été analysé à ce jour. Cette étude s’intéresse au lien entre la socialisation religieuse et la religiosité actuelle, et à leur impact sur la probabilité d’agrandissement de deux à trois enfants de la descendance des femmes néerlandaises. Les données exploitées sont celles de la première vague du Panel Néerlandais d’Etude de la Parenté (the Netherlands Kinship Panel Study, 2002–2004). A l’aide des techniques de l’analyse des biographies, les probabilités d’agrandissement de rang 1, rang 2 et rang 3 ont été modélisées de façon conjointe, en contrôlant l’hétérogénéité non observée. Les résultats mettent en évidence l’impact de la fréquentation actuelle de l’église par les femmes et de leur socialisation religieuse, mesurée par l’appartenance religieuse de leur père quand elles étaient adolescentes. Il apparaît que la religiosité du contexte familial exerce une influence, même quand la femme ne fréquente plus l’église, et que les effets des indicateurs de pratique religieuse se renforcent d’une génération à l’autre. Enfin, l’appartenance religieuse conjointe des parents de la femme détermine significativement la probabilité d’avoir un troisième enfant

Ontkerkelijking: oorzaken en gevolgen

Contains fulltext : 145557.pdf (Publisher’s version ) (Open Access)177 p

De invloed van inkomensongelijkheid en rationalisering op kerkverlating in Nederland tussen 1975 en 1995

Contains fulltext : 99229.pdf (publisher's version ) (Open Access)The effects of economic inequality and modernization on religious disaffiliation. A test for the Netherlands in 1975-1995 In a recent study, using data from 60 nations, Ruiter and Van Tubergen (2009) found individuals from countries with highest economic inequalities to run the lowest risk of religious disaffiliation. Interestingly, modernization was found to have no effect on religious disaffiliation. A more stringent test is to investigate how economic inequality and modernization are related to religious disaffiliation within countries over time. In this study we use data from the Netherlands gathered between 1975-1995, a period in which religious disaffiliation was prominent. Our main findings run counter to those of Ruiter and Van Tubergen. In the Netherlands, higher levels of economic inequality and higher levels of modernization seem to increase religious disaffiliation.25 p

De gevolgen van de-institutionalisering, rationalisering en privatisering voor culturele individualisering

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