Detecting inattentive respondents by machine learning: A generic technique that substitutes for the directed questions scale and compensates for its shortcomings.

Web surveys are often used to collect data for psychological research. However, the inclusion of many inattentive respondents can be a problem. Various methods for detecting inattentive respondents have been proposed, most of which require the inclusion of additional items in the survey for detection or the calculation of variables for detection after data collection. This study proposes a method for detecting inattentive respondents in web surveys using machine learning. The method requires only the collection of response time and the inclusion of a Likert scale, eliminating the need to include special detection items in the survey. Based on data from 16 web surveys, a method was developed using predictor variables not included in existing methods. While previous machine learning methods for detecting inattentive respondents can only be applied to the same surveys as the data on which the models were developed, the proposed model is generic and can be applied to any questionnaire as long as response time is available, and a Likert scale is included. In addition, the proposed method showed partially higher accuracy than existing methods.

Psychosocial Twin Cohort Studies in Japan: The Keio Twin Research Center (KoTReC).

The Keio Twin Research Center (KoTReC) was established in 2009 at Keio University to combine two longitudinal cohort projects - the Keio Twin Study (KTS) for adolescence and adulthood and the Tokyo Twin Cohort Project (ToTCoP) for infancy and childhood. KoTReC also conducted a two-time panel study of self-control and psychopathology in twin adolescence in 2012 and 2013 and three independent anonymous cross-sectional twin surveys (ToTcross) before 2012 - the ToTCross, the Junior and Senior High School Survey and the High School Survey. This article introduces the recent research designs of KoTReC and its publications.

A New Look at Genetic and Environmental Architecture on Lipids Using Non-Normal Structural Equation Modeling in Male Twins: The NHLBI Twin Study.

This study examined genetic and environmental influences on the lipid concentrations of 1028 male twins using the novel univariate non-normal structural equation modeling (nnSEM) ADCE and ACE models. In the best fitting nnSEM ADCE model that was also better than the nnSEM ACE model, additive genetic factors (A) explained 4%, dominant genetic factors (D) explained 17%, and common (C) and unique (E) environmental factors explained 47% and 33% of the total variance of high-density lipoprotein cholesterol (HDL-C). The percentage of variation explained for other lipids was 0% (A), 30% (D), 34% (C) and 37% (E) for low-density lipoprotein cholesterol (LDL-C); 30, 0, 31 and 39% for total cholesterol; and 0, 31, 12 and 57% for triglycerides. It was concluded that additive and dominant genetic factors simultaneously affected HDL-C concentrations but not other lipids. Common and unique environmental factors influenced concentrations of all lipids.

Genetic and Environmental Influences on Traits of Gender Identity Disorder: A Study of Japanese Twins Across Developmental Stages.

The present study examined: (1) gender and age differences of mean gender identity disorder (GID) trait scores in Japanese twins; (2) the validity of the prenatal hormone transfer theory, which predicts that, in dizygotic (DZ) twin pairs, twins with an opposite-gender co-twin more frequently exhibit GID traits than twins with a same-gender co-twin; and (3) the magnitude of genetic and environmental influences on GID traits as a function of age and gender. Data from 1450 male twin pairs, 1882 female twin pairs, and 1022 DZ male-female pairs ranging from 3 to 26 years of age were analyzed. To quantify individual variances in GID traits, each participant completed four questionnaire items based on criteria for GID from the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV-TR). Our most important findings were: (1) Japanese females exhibited GID traits more frequently than males and Japanese children exhibited GID traits less frequently than adolescents and adults (among females, the prevalence was 1.6 % in children, 10 % in adolescents, and 12 % in adults; among males, the prevalence was 0.5, 2, and 3 %, respectively); (2) the data did not support the prenatal hormone transfer theory for GID traits; and (3) a large part of the variance for GID traits in children was accounted for by familial factors; however, the magnitude was found to be greater in children than in adolescents or adults, particularly among females. This study suggests that although the prevalence is likely to increase, familial effects are likely to decrease as individuals age.

Joint and independent effect of alcohol and tobacco use on the risk of subsequent cancer incidence among cancer survivors: A cohort study using cancer registries.

Drinking alcohol and smoking tobacco are major modifiable risk factors for cancer. However, little is known about whether these modifiable factors of cancer survivors are associated with subsequent primary cancer (SPC) incidence, regardless of the first cancer sites. 27,762 eligible cancer survivors diagnosed between 1985 and 2007 were investigated for SPC until the end of 2008, using hospital-based and population-based cancer registries. The association between drinking, smoking and combined drinking and smoking (interaction) at the time of the first cancer diagnosis and incidence of SPCs (i.e., all SPCs, alcohol-related, smoking-related and specific SPCs) was estimated by Poisson regression. Compared with never-drinker/never-smoker, the categories ever-drinker/ever-smoker, current-drinker/current-smoker and heavy-drinker/heavy-smoker had 43-108%, 51-126% and 167-299% higher risk for all, alcohol-related and tobacco-related SPCs, respectively. The interaction of drinking and smoking had significantly high incidence rate ratios (IRRs) for SPCs among ever-drinker/ever-smoker and current-drinker/current-smoker, although ever drinking did not show a significant risk. Ever-drinker/ever-smoker had also significantly higher IRRs for esophageal and lung SPCs than never-drinker/never-smoker. Among comprehensive cancer survivors, ever and current drinkers only had a SPC risk when combined with smoking, while ever and current smokers had a SPC risk regardless of drinking status. Heavy drinking and heavy smoking were considered to be independent additive SPC risk factors. To reduce SPC incidence, it may be necessary (i) to reduce or stop alcohol use, (ii) to stop tobacco smoking and (iii) dual users, especially heavy users, should be treated as a high-risk population for behavioral-change intervention.

Bidirectional influences between maternal parenting and children's peer problems: a longitudinal monozygotic twin difference study.

This twin study examined the bidirectional relationship between maternal parenting behaviors and children's peer problems that were not confounded by genetic and family environmental factors. Mothers of 259 monozygotic twin pairs reported parenting behaviors and peer problems when twins were 42 and 48 months. Path analyses on monozygotic twin difference scores revealed that authoritative parenting (the presence of consistent discipline and lack of harsh parenting) and peer problems simultaneously influenced each other. Authoritative parenting reduced peer problems, and peer problems increased authoritative parenting. Neither consistent discipline nor harsh parenting alone was associated with peer problems. These results suggest that maternal authoritative parenting works protectively in regard to children's peer problems, and peer problems can evoke such effective parenting.

Two cohort and three independent anonymous twin projects at the Keio Twin Research Center (KoTReC).

The Keio Twin Research Center has conducted two longitudinal twin cohort projects and has collected three independent and anonymous twin data sets for studies of phenotypes related to psychological, socio-economic, and mental health factors. The Keio Twin Study has examined adolescent and adult cohorts, with a total of over 2,400 pairs of twins and their parents. DNA samples are available for approximately 600 of these twin pairs. The Tokyo Twin Cohort Project has followed a total of 1,600 twin pairs from infancy to early childhood. The large-scale cross-sectional twin study (CROSS) has collected data from over 4,000 twin pairs, from 3 to 26 years of age, and from two high school twin cohorts containing a total of 1,000 pairs of twins. These data sets of anonymous twin studies have mainly targeted academic performance, attitude, and social environment. The present article introduces the research designs and major findings of our center, such as genetic structures of cognitive abilities, personality traits, and academic performances, developmental effects of genes and environment on attitude, socio-cognitive ability and parenting, genes x environment interaction on attitude and conduct problem, and statistical methodological challenges and so on. We discuss the challenges in conducting twin research in Japan.

Genetic and environmental relationships between head circumference growth in the first year of life and sociocognitive development in the second year: a longitudinal twin study.

Although growth in head circumference (HC) during infancy is known to predict later childhood outcomes, the mechanisms underlying this association with later sociocognitive abilities remain undetermined. Thus, using a sample of 241 pairs of normally developing Japanese twins, this study investigated the underpinnings of the association between HC growth (difference between HC at birth and at 10 months) and sociocognitive abilities at 19 months as measured by 10 items from the M-CHAT. Phenotypic correlations between HC at birth and sociocognitive abilities and between HC growth and sociocognitive abilities were marginal and not significant. However, multivariate genetic analyses using Cholesky decomposition revealed that genetic influences on HC growth and those on sociocognitive abilities were negatively associated. On the other hand, shared and nonshared environmental influences on HC growth were positively associated with influences on sociocognitive abilities. Genetic and environmental influences on HC at birth were not significantly associated with influences on sociocognitive abilities. These results help to clarify the role of brain growth during infancy in the subsequent development of sociocognitive abilities and highlight the importance of examining the different roles of genetic and environmental influences in studies of these areas.

Using non-normal SEM to resolve the ACDE model in the classical twin design.

One of the biggest problems in classical twin studies is that it cannot estimate additive genetic (A), non-additive genetic (D), shared environmental (C), and non-shared environmental (E) effects, simultaneously, because the model, referred to as the ACDE model, has negative degrees of freedom when using Structural Equation Modeling (SEM). Therefore, instead of the ACDE model, the ACE model or the ADE model is actually used. However, using the ACE or ADE models almost always leads to biased estimates. In the present paper, the univariate ACDE model is developed using non-normal Structural Equation Modeling (nnSEM). In SEM, (1st- and) 2nd-order moments, namely, (means and) covariances are used as information. However, nnSEM uses higher-order moments as well as (1st- and) 2nd-order moments. nnSEM has a number of advantages over SEM. One of which is that nnSEM can specify models that cannot be specified using SEM because of the negative degrees of freedom. Simulation studies have shown that the proposed method can decrease the biases. There are other factors that have possible effects on phenotypes, such as higher-order epistasis. Since the proposed method cannot estimate these effects, further research on developing a more exhaustive model is needed.

Analyzing Upward Deviation of Actual vs Predicted Drug Sales in Japan for a Reasonable Drug-Pricing Policy.

BACKGROUND: Predictions of drug sales play an important role in setting drug prices in Japan, where drug prices are highly regulated. One of 2 primary Japanese drug-pricing methodologies-the cost calculation method- refers extensively to the prediction of drug sales in establishing drug prices. Deviations from predicted sales can induce disproportionate drug prices and unexpected pharmaceutical expenditures. This study aimed to estimate the upward deviation of actual sales from predicted sales and to explore the predictors of such upward deviation. METHODS: Estimates of upward deviation in 2015 were produced for new molecular entities (NMEs) approved in 2006-2015. To identify the predictors associated with upward deviation through binary logistic regression analyses, sales within 3 years of launch and in the predicted year in which peak sales would be reached were used. RESULTS: Estimated upward deviation was more than 1220 billion yen in 2015 for the targeted drugs. Drugs priced by the cost calculation method or by obtaining additional indications were significantly more likely to show an upward deviation from predicted peak sales. CONCLUSIONS: There is substantial upward deviation between actual and predicted drug sales in Japan. So long as drug sales predictions are used in drug price calculations, a flexible repricing system is needed to buffer unexpected pharmaceutical expenditures.

A Comparative Study of the Market Configuration of the Japanese Pharmaceutical Market Using the Gini Coefficient and Herfindahl-Hirschman Index.

BACKGROUND: As of 2015, the Japanese pharmaceutical market was the world's third largest pharmaceutical market. Although previous studies have examined market differences in terms of market size and pricing policy, little is known about comparative market configurations. The present study provides a comparative analysis of pharmaceutical market configurations in Japan and five other markets. METHODS: Based on data for the 100 top-selling drugs in 2014 in Japan, the United States, the United Kingdom, France, Germany, and the global market, we explored differences in market configurations using the Herfindahl-Hirschman Index, Lorenz curves, and Gini coefficients. We also investigated market trends by analyzing changes in sales, sales volume, and price. RESULTS: The 100 top-selling drugs accounted for a lower share of the total market in Japan, France, and Germany as compared to the United States and the United Kingdom. The market deviation of the 100 top-selling drugs indicated by the Herfindahl-Hirschman Index and Gini coefficient was smallest in Japan. Sales of most of the top-100 drugs increased in all the countries studied; however, directional price changes differed by country and sales volume trend. CONCLUSION: Our findings showed that market deviations in Japan were relatively low compared with those in other developed countries, suggesting that some of the more beneficial drugs in other developed countries obtain relatively fewer benefits from the Japanese pharmaceutical market, and some less beneficial drugs obtained more benefits.

Genetic correlation between autistic traits and IQ in a population-based sample of twins with autism spectrum disorders (ASDs).

Although there is accumulating evidence that intelligence quotient (IQ) indexes some aspects of the autistic spectrum disorders (ASDs), the causal relationship between autistic traits and IQ remains controversial. We examined the sources of covariation between autistic traits and IQ. As males have a four times greater risk of ASDs than females, gender-specific effects were also explored. Autistic traits and IQ were assessed in 45 twin male-male, female-female and opposite-sex pairs ascertained by the regional screening system in Nagoya, Japan. Sex-limited Cholesky structural equation models were used to decompose the correlations between autistic traits and IQ into genetic and environmental components, including sex-specific factors. Genetic correlations between autistic traits and IQ were high and not significantly different between boys and girls (-0.94 and -0.95, respectively), but genetic factors underlying the autistic traits were not entirely shared with the IQ. The individual-specific environmental correlation between autistic traits and IQ was estimated at -0.29 for boys and -0.59 for girls. There is a substantial overlap between the genetic factors that influence individual variation in autistic traits and IQ, irrespective of gender. The individual life experiences that increase autistic traits, however, have a moderate overlap with those that contribute to individual IQs.

Direction of causation between shared and non-shared environmental factors.

Determining the direction of causation between two related variables is an interesting and challenging problem. A simple regression model is a frequently used statistical tool to find out whether a dependent variable is significantly predicted by an independent variable; however using a simple regression model cannot determine the direction of causation, because the model fit takes no account of this direction. As an approach to this problem, non-normal structural equation modeling (nnSEM; Shimizu and Kano, J Stat Plan Inference 138:3483-3491, 2008) using higher order moments (third, fourth,...) as well as first and second order moments, can be useful. This method enables us to determine the direction of causation using goodness of fit, even for a simple regression model. In this paper, nnSEM is applied to behavior genetics, in particular, to the genetic simplex model. In this context, nnSEM enables us to determine the direction of causation between C (shared environment) factors and between E (non-shared environment) factors. The efficiency of this method is illustrated by simulation studies and the analysis of real longitudinal twin data.

[Gender differences in genetic and environmental etiology of gender role personality (BSRI)].

This study investigated the possible effects of genetic and environmental gender differences in effect on individual differences by using the Bem Sex Role Inventory (BSRI) with twins. A sex/gender-limitation analysis, a behavior genetics methodology was used to the following: (a) effects of gender-specific genes, (b) gender differences in quantitative genetic effects, (c) effects of gender-specific shared environment, (d) gender differences of quantitative shared environment, and (e) gender differences of quantitative nonshared environment. Participants were adolescent and adult twins, including 111 identical male pairs, 241 identical female pairs, 36 fraternal male pairs, 65 fraternal female pairs, and 58 opposite-gender pairs. The results indicated that although masculinity and femininity were explained by genetic factors to some extent, there were no significant gender differences in the genetic factors. Moreover, because our data did not support a model which explained gender differences in the effects of specific common environment factors, no evidence was found to support the prenatal hormonal hypothesis or the existence of parenting which encouraged children's gender role personality.

Analyzing Upward Deviation of Actual vs Predicted Drug Sales in Japan for a Reasonable Drug-Pricing Policy.

BACKGROUND: Predictions of drug sales play an important role in setting drug prices in Japan, where drug prices are highly regulated. One of 2 primary Japanese drug-pricing methodologies-the cost calculation method- refers extensively to the prediction of drug sales in establishing drug prices. Deviations from predicted sales can induce disproportionate drug prices and unexpected pharmaceutical expenditures. This study aimed to estimate the upward deviation of actual sales from predicted sales and to explore the predictors of such upward deviation. METHODS: Estimates of upward deviation in 2015 were produced for new molecular entities (NMEs) approved in 2006-2015. To identify the predictors associated with upward deviation through binary logistic regression analyses, sales within 3 years of launch and in the predicted year in which peak sales would be reached were used. RESULTS: Estimated upward deviation was more than 1220 billion yen in 2015 for the targeted drugs. Drugs priced by the cost calculation method or by obtaining additional indications were significantly more likely to show an upward deviation from predicted peak sales. CONCLUSION: There is substantial upward deviation between actual and predicted drug sales in Japan. So long as drug sales predictions are used in drug price calculations, a flexible repricing system is needed to buffer unexpected pharmaceutical expenditures.

[Graphical modeling for constructs: an integrated solution for factor analysis and GM].

This research develops a new method for analyzing relation for factors which combines graphical modeling (GM) and factor analysis. In this method, estimation of the inverse of the variance-covariance matrix is done in the framework of factor analysis, and then the data-model fit is investigated using GM. The partial correlation coefficients of the estimated model are calculated, and the estimation of parameters is repeated until discovery of the worst fit index. In order to confirm the effectiveness of this method, three correlation matrices were analyzed as a real data study. In first and second case, intelligence models of Harman and Turstone were restructured using this method. In third case, EQ model was structured using it. The results show that this method can be apply GM for latent variables and a good assistant to set up path models for factors.

The Tokyo Twin Cohort Project: overview and initial findings.

The Tokyo Twin Cohort Project (ToTCoP) is a large-scale longitudinal study of 5 years based on 1619 pairs of infant twins reared together. The purpose of the study is to construct a population-based twin registry in Japan and to investigate human growth and development and twin themselves. It covers behavioral, neurological, physical and environmental variables measured by questionnaire, home visiting and brain imaging technology. The full registry contains over 47,000 multiple births collected from the Basic Resident Register, and the targeted population is 3070 probable twins of 0 to 2 years old. Preliminary analysis of the entry questionnaire data showed no serious sampling biases. Descriptive statistics of parental characteristics (parental age, gestation age, parity and placentation, maternal weight, parenting stress) and children's characteristics (body size at birth, 4 and 10 months of age, milk consumption, and sleeping and social behavior) and their correlations, genetic and environmental contributions and correlations are reported.

[Comparison of several expressions of two-way ANOVA for a latent factor: analysis of the relation between music and mood].

The purpose of this research is to provide a two-way analysis of variance (ANOVA) model for a latent factor. Typical psychological studies measure mental states with questionnaires and analyze the variance of the measures into the portions attributable to various sources. This type of research, when conducted under regular ANOVA designs, uses total score as the dependent measures. However, this method is based on the unrealistic presumption that every item on the questionnaire has the same factor loading on the attribute being measured. In this research, we incorporated factor analysis model, and used a latent factor instead of total score as the dependent measure, thereby applying ANOVA under a more realistic assumption. Structural Equation Modeling (SEM) was used to express statistical models. This paper also examined a relation between music and mood, which is a quite popular area of research in psychology of music. To study the possible effects of tonality and key-signature on mood, music was chosen to represent tonality and key-signature conditions.

DINA Models for Multiple-Choice Items With Few Parameters: Considering Incorrect Answers.

The deterministic-input, noisy "and" gate (DINA) model can judge whether an individual examinee has mastered each skill that is needed to answer an item correctly. This information is useful for students to know their deficits and for teachers to teach effectively. The DINA model is a statistical model for binary (correct or incorrect) data. However, recently a DINA model for multiple-choice items was developed by de la Torre. The model is aimed at obtaining information about students' skills from incorrect answers. In the present study, new DINA models for multiple-choice items are developed that need many fewer parameters while still being able to express various answering probabilities without any restrictions on the form of the Q-matrix. Simulations using a Markov chain Monte Carlo method are performed to demonstrate the efficacies of the proposed models compared with the DINA model for binary data and the model of de la Torre for multiple-choice items, if appropriate starting values are set.

Maternal and paternal indoor or outdoor smoking and the risk of asthma in their children: a nationwide prospective birth cohort study.

BACKGROUND: Little is known about the differential impact of combinations of parental smoking behavior (indoor or outdoor smoking, or not smoking) on preventing childhood asthma. Our objective was to examine the association between parental smoking behavior and children's asthma. METHODS: A nationally representative population-based birth cohort of 40,580 babies, aged 0.5 years in 2001 (response rate, 87.8%), was studied to estimate adjusted odds ratios of combinations of maternal and paternal indoor or outdoor smoking at home for physician visits and hospitalization for childhood asthma up to 8-years-old, and population attributable fractions. RESULTS: Odds of hospitalization for asthma among children whose father alone smokes indoors at home did not largely increase (up to 20%). However, if the mother also smokes indoors at home, the odds strongly increased. After adjusting for demographic, perinatal and socioeconomic factors, the increase in odds for children whose father and mother both smoke indoors compared to children with non-smoking parents was 54% (95% confidence interval: 21-96%), 43% (8-90%) and 72% (22-143%) for children aged 0.5<-2.5, 2.5<-4.5 and 4.5<-8 years-old, respectively. The odds ratios of smoking outdoors did not largely differ from those of smoking indoors. Our estimation of population attributable fractions revealed that if all parents in Japan quit smoking, hospitalization of children for asthma could be reduced by 8.3% (2.2-14.3%), 9.3% (0.9-17.6%) and 18.2% (7.7-28.8%), respectively. CONCLUSIONS: Parental indoor smoking at home increased and exacerbated children's asthma. Smoking at home, whether it is indoors or outdoors, may increase the risks for asthma attacks of their children.