scholarly journals Parental criticism and adolescent internalising symptoms: using a Children‐of‐Twins design with power calculations to account for genetic influence

2021 ◽  
Author(s):  
Yasmin I. Ahmadzadeh ◽  
Thalia C. Eley ◽  
Laurie Hannigan ◽  
Cathy Creswell ◽  
Paul Lichtenstein ◽  
...  
Keyword(s):  
Genetic Influence ◽  
Parental Criticism ◽  
Power Calculations ◽  
Children Of Twins

scholarly journals Parental criticism and adolescent internalising symptoms: Associations remain after accounting for shared genetic effects

2020 ◽  
Author(s):  
Yasmin I Ahmadzadeh ◽  
Thalia C Eley ◽  
Laurie J. Hannigan ◽  
Cathy Creswell ◽  
Paul Lichtenstein ◽  
...  
Keyword(s):  
Structural Equation ◽  
Statistical Power ◽  
Structural Equation Models ◽  
Genetic Relatedness ◽  
Genetic Effects ◽  
Psychosocial Effects ◽  
Parental Criticism ◽  
Adolescent Offspring ◽  
Children Of Twins ◽  
Small Models

AbstractObjectiveParental criticism is associated with internalising symptoms in adolescent offspring. It is unclear whether these behaviours cause one another, and/or whether they are influenced by shared genes in related parent-offspring pairs. We use an Extended Children of Twins design to assess whether parent-reported criticism and offspring internalising symptoms remain associated after controlling for shared genes. To aid interpretation of our results and those of previous Children of Twins studies, we examine statistical power for the detection of genetic effects and explore the direction of psychosocial influences between generations.MethodData were drawn from two Swedish twin samples, comprising 876 adult twin pairs with adolescent offspring and 1030 adolescent twin pairs with parents. Parents reported on criticism towards their offspring, concurrently with parent and offspring reports of adolescent internalising symptoms. Extended Children of Twins structural equation models were used to examine intergenerational social and genetic mechanisms.ResultsParental criticism was associated with adolescent internalising symptoms after controlling for genetic relatedness. No significant role was found for shared genes influencing phenotypes in both generations. Power analyses confirmed that any undetected genetic effects were small. Models could not distinguish the causal direction of possible psychosocial effects between generations.ConclusionThe association between parent-reported criticism and adolescent internalising symptoms is not attributable to genetic confounding in this sample. As such, parental criticism may be involved in psychosocial family processes in the context of adolescent internalising. Future studies should seek to identify these processes and provide clarity on the direction of potential causal effects.

Shared Genetic Influence on Early Growth and Type 2 Diabetes in Adulthood

Diabetes ◽  
2018 ◽  
Vol 67 (Supplement 1) ◽  
pp. 18-OR
Author(s):  
FASIL TEKOLA-AYELE ◽  
ANTHONY LEE ◽  
TSEGASELASSIE WORKALEMAHU ◽  
DEEPIKA SHRESTHA
Keyword(s):  
Type 2 Diabetes ◽  
Early Growth ◽  
Genetic Influence ◽  
Shared Genetic

Simulation-based power calculations for conjoint experiments

2020 ◽  
Author(s):  
Brett J. Gall
Keyword(s):  
Power Calculations ◽  
Simulation Based ◽  
Different Types ◽  
Power Analyses

I introduce code for each step required to conduct power analyses through simulation in R, with special attention to the challenges of conjoint experiments. We’ll slowly build up our code until we have something that fairly easily can simulate power of different types of conjoint experiments. The goal is provide enough detail and intuition to write up your own custom simulations.

Identification of Distinct Etiologies across Prescription Misuse and Illicit Drug Use: Opioids and Stimulants Compared

2020 ◽  
Author(s):  
Genevieve Fullerton Dash ◽  
Nicholas G. Martin ◽  
Arpana Agrawal ◽  
Michael Lynskey ◽  
Wendy S. Slutske
Keyword(s):  
Illicit Drugs ◽  
Genetic Influence ◽  
Prescription Opioid ◽  
Future Research ◽  
Opioid Use ◽  
Stimulant Use ◽  
Drug Classes ◽  
Illicit Use ◽  
Prescription Opioid Misuse ◽  
Illicit Opioid Use

Background. Drug classes are grouped based on their chemical and pharmacological properties, but prescription and illicit drugs differ in other important ways. Opioid and stimulant classes contain prescription and illicit forms differentially associated with salient risk factors (common route of administration, legality), making them useful comparators for examining the potential differences in the etiological influences on (mis)use of prescription and illicit drugs. Methods. 2,410 individual Australian twins (Mage=31.77 [SD=2.48]; 67% women) were interviewed about prescription misuse and illicit use of opioids and stimulants. Univariate and bivariate biometric models partitioned variances and covariances into additive genetic, shared environmental, and unique environmental influences across drug types. Results. Variation in the propensity to misuse prescription opioids was primarily attributable to genes (37%) and unique environment (59%). Illicit opioid use was attributable to shared (71%) and unique (29%) environment. Prescription stimulant misuse was primarily attributable to genes (78%) and unique environment (21%). Illicit stimulant use was influenced by genes (48%), and shared (29%) and unique environment (23%). There was evidence for genetic influence common to both stimulant types, but limited evidence for genetic influence common to both opioid types. Conclusions. Prescription opioid misuse may share little genetic influence with illicit opioid use. Future research may consider avoiding unitary drug classifications, particularly when examining genetic influences.

scholarly journals Estimates of the mean difference in orthopaedic randomized trials: obligatory yet obscure

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Lauri Raittio ◽  
Antti Launonen ◽  
Ville M. Mattila ◽  
Aleksi Reito
Keyword(s):  
Primary Outcome ◽  
Outcome Measure ◽  
Patient Reported Outcome ◽  
Ceiling Effect ◽  
Mean Difference ◽  
Discussion Section ◽  
Power Calculations ◽  
Randomized Controlled ◽  
Patient Reported ◽  
The Mean

Abstract Background Randomized controlled trials in orthopaedics are powered to mainly find large effect sizes. A possible discrepancy between the estimated and the real mean difference is a challenge for statistical inference based on p-values. We explored the justifications of the mean difference estimates used in power calculations. The assessment of distribution of observations in the primary outcome and the possibility of ceiling effects were also assessed. Methods Systematic review of the randomized controlled trials with power calculations in eight clinical orthopaedic journals published between 2016 and 2019. Trials with one continuous primary outcome and 1:1 allocation were eligible. Rationales and references for the mean difference estimate were recorded from the Methods sections. The possibility of ceiling effect was addressed by the assessment of the weighted mean and standard deviation of the primary outcome and its elaboration in the Discussion section of each RCT where available. Results 264 trials were included in this study. Of these, 108 (41 %) trials provided some rationale or reference for the mean difference estimate. The most common rationales or references for the estimate of mean difference were minimal clinical important difference (16 %), observational studies on the same subject (8 %) and the ‘clinical relevance’ of the authors (6 %). In a third of the trials, the weighted mean plus 1 standard deviation of the primary outcome reached over the best value in the patient-reported outcome measure scale, indicating the possibility of ceiling effect in the outcome. Conclusions The chosen mean difference estimates in power calculations are rarely properly justified in orthopaedic trials. In general, trials with a patient-reported outcome measure as the primary outcome do not assess or report the possibility of the ceiling effect in the primary outcome or elaborate further in the Discussion section.

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