Latent variable mixture modeling is a technique that is useful to pediatric psychologists who wish to find groupings of individuals who share similar data patterns to determine the extent to which these patterns may relate to variables of interest.
Pathological alcohol use is a complex and costly problem. This chapter focuses on recent developments in the etiology of alcohol use disorders. Literature is reviewed from the fields of epidemiology, genetics, personality, neuropsychology, parenting, and social influences. In addition, theoretical models that describe pathways to the development of alcohol use disorders are presented. Particular emphasis is given to ways in which genetic, environmental, psychopharmacological, and personological literatures can inform one another.
Latent variable mixture modeling is a technique that is useful to pediatric psychologists who wish to find groupings of individuals who share similar longitudinal data patterns to determine the extent to which these patterns may relate to variables of interest.
Aim The aim of this study is to answer the questions: (1) do small organisms disperse farther than large, or vice versa; and (2) does the observed pattern differ for passive and active dispersers? These questions are central to several themes in biogeography (including microbial biogeography), macroecology, metacommunity ecology and conservation biology.Location The meta-analysis was conducted using published data collected worldwide.
MethodsWe collected and analysed 795 data values in the peer-reviewed literature for direct observations of both maximal dispersal distance and mass of the dispersing organisms (e.g. seeds, not trees). Analysed taxa ranged in size from bacteria to whales. We applied macroecology analyses based on null models (using Monte Carlo randomizations) to test patterns relative to specific hypotheses.
ResultsCollected dispersal distance and mass data spanned 9 and 21 orders of magnitude, respectively. Active dispersers dispersed significantly farther ( P < 0.001) and were significantly greater in mass ( P < 0.001) than passive dispersers. Overall, size matters: larger active dispersers attained greater maximum observed dispersal distances than smaller active dispersers. In contrast, passive-disperser distances were random with respect to propagule mass, but not uniformly random, in part due to sparse data available for tiny propagules.
ConclusionsSize is important to maximal dispersal distance for active dispersers, but not for passive dispersers. Claims that microbes disperse widely cannot be tested by current data based on direct observations of dispersal: indirect approaches will need to be applied. Distance-mass relationships should contribute to a resolution of neutral and niche-based metacommunity theories by helping scale expectations for dispersal limitation. Also, distance-mass relationships should inform analyses of latitudinal species richness and conservation biology topics such as fragmentation, umbrella species and taxonomic homogenization.
This study examined the role of demographic characteristics, psychological factors, and family functioning on attendance in a randomized controlled trial of a family-based pediatric obesity program.
Participants included 155 children between the ages of 4 and 7 years (M age = 5.77, 57.4% female, 73.6% African-American, M BMI = 25.5) and their primary caregivers who were randomized to the treatment group. Three groups of participants were created based on their patterns of attendance during the program: 1) noncompleters, 2) partial completers, and 3) completers.
Results indicated no differences among the attendance groups in child gender, child BMI, or child psychological functioning. Significant group differences were found with respect to race/ethnicity, parent marital status, and family income, such that noncompleters were more likely to be racial/ethnic minorities, to living in single parent households, and to have lower incomes than partial completers and completers. After controlling for the effects these socio-demographic risk factors, noncompleters and partial completers reported more family dysfunction characterized by high levels of disengagement than completers.
Adapting existing weight management programs to include a focus on family engagement in the early stages of treatment may help to improve participation in family-based obesity interventions targeting high risk, socio-economically disadvantaged youth.
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