Potential predictors in neonaticide: the impact of the circumstances of pregnancy.

This study aims to evaluate the psychosocial factors of neonaticide, especially the circumstances before delivery, the relationships of the pregnant women, and their social environment awareness of women's pregnancy. This nationwide study was register-based, comprising all known neonaticides in Austria and Finland between 1995 and 2005. Cases (n = 28) were obtained by screening the death certificates from coroner's departments and by analyzing them along with all further available reports. Few women (17.9 %, 5/28) admitted their pregnancy to others. Although most (16/28) offenders were in a relationship, the partner had knowledge of the pregnancy in only three cases. The main motive for negation of the pregnancy (named in 60.8 % of cases) was fear of abandonment/negative response from others. The fertility rate among the women was high, but half of those with children had lost the custody of them. In neonaticide, the lack of awareness surrounding offenders' pregnancy, as well as the awareness of social environment, is more relevant than any other social variable.

Sensitivity to initial values in full non-parametric maximum-likelihood estimation of the two-parameter logistic model.

Parameters of the two-parameter logistic model are generally estimated via the expectation-maximization (EM) algorithm by the maximum-likelihood (ML) method. In so doing, it is beneficial to estimate the common prior distribution of the latent ability from data. Full non-parametric ML (FNPML) estimation allows estimation of the latent distribution with maximum flexibility, as the distribution is modelled non-parametrically on a number of (freely moving) support points. It is generally assumed that EM estimation of the two-parameter logistic model is not influenced by initial values, but studies on this topic are unavailable. Therefore, the present study investigates the sensitivity to initial values in FNPML estimation. In contrast to the common assumption, initial values are found to have notable influence: for a standard convergence criterion, item discrimination and difficulty parameter estimates as well as item characteristic curve (ICC) recovery were influenced by initial values. For more stringent criteria, item parameter estimates were mainly influenced by the initial latent distribution, whilst ICC recovery was unaffected. The reason for this might be a flat surface of the log-likelihood function, which would necessitate setting a sufficiently tight convergence criterion for accurate recovery of item parameters.

Developmental Steps in Metaphorical Language Abilities: The Influence of Age, Gender, Cognitive Flexibility, Information Processing Speed, and Analogical Reasoning.

PURPOSE: Metaphor is a specific type of figurative language that is used in various important fields such as in the work with children in clinical or teaching contexts. The aim of the study was to investigate the developmental course, developmental steps, and possible cognitive predictors regarding metaphor processing in childhood and early adolescence. METHOD: One hundred sixty-four typically developing children (7-year-olds, 9-year-olds) and early adolescents (11-year-olds) were tested for metaphor identification, comprehension, comprehension quality, and preference by the Metaphoric Triads Task as well as for analogical reasoning, information processing speed, cognitive flexibility under time pressure, and cognitive flexibility without time pressure. RESULTS: Metaphor identification and comprehension consecutively increased with age. Eleven-year-olds showed significantly higher metaphor comprehension quality and preference scores than seven- and nine-year-olds, whilst these younger age groups did not differ. Age, cognitive flexibility under time pressure, information processing speed, analogical reasoning, and cognitive flexibility without time pressure significantly predicted metaphor comprehension. CONCLUSIONS: Metaphorical language ability shows an ongoing development and seemingly changes qualitatively at the beginning of early adolescence. These results can possibly be explained by a greater synaptic reorganization in early adolescents. Furthermore, cognitive flexibility under time pressure and information processing speed possibly facilitate the ability to adapt metaphor processing strategies in a flexible, quick, and appropriate way.

Birthday and birthmate problems: misconceptions of probability among psychology undergraduates and casino visitors and personnel.

Subjective estimates and associated confidence ratings for the solutions of some classic occupancy problems were studied in samples of 721 psychology undergraduates, 39 casino visitors, and 34 casino employees. On tasks varying the classic birthday problem, i.e., the probability P for any coincidence among N individuals sharing the same birthday, clear majorities of respondents markedly overestimated N, given P, and markedly underestimated P, given N. Respondents did notedly better on tasks varying the birthmate problem, i.e., P for the specific coincidence among N individuals of having a birthday today. Psychology students and women did better on both task types, but were less confident about their estimates than casino visitors or per sonnel and men. Several further person variables, such as indicators of topical knowledge and familiarity, were associated with better and more confident performance on birthday problems, but not on birthmate problems. Likewise, higher confidence ratings were related to subjective estimates that were closer to the solutions of birthday problems, but not of birthmate problems. Implications of and possible explanations for these findings, study limitations, directions for further inquiry, and the real-world relevance of ameliorating misconceptions of probability are discussed.

Testing the Rasch model by means of the mixture fit index.

Rudas, Clogg, and Lindsay (RCL) proposed a new index of fit for contingency table analysis. Using the overparametrized two-component mixture, where the first component with weight 1-w represents the model to be tested and the second component with weight w is unstructured, the mixture index of fit was defined to be the smallest w compatible with the saturated two-component mixture. This index of fit, which is insensitive to sample size, is applied to the problem of assessing the fit of the Rasch model. In this application, use is made of the equivalence of the semi-parametric version of the Rasch model to specifically restricted latent class models. Therefore, the Rasch model can be represented by the structured component of the RCL mixture, with this component itself consisting of two or more subcomponents corresponding to the classes, and the unstructured component capturing the discrepancies between the data and the model. An empirical example demonstrates the application of this approach. Based on four-item data, the one- and two-class unrestricted latent class models and the one- to three-class models restricted according to the Rasch model are considered, with respect to both their chi-squared statistics and their mixture fit indices.

The Miandad effect reconsidered: analysis of Pakistan's cricket performance 1952 to 2005.

In 2004 Abbasi and Khan reported an enduring influence of a 1986 Pakistani landmark victory in cricket over India on subsequent matches up to 2003. The present study reconsidered the significance and the specificity of this phenomenon, denoted as the "Miandad effect." All 659 Pakistani cricket encounters with India and other frequently played opponents up to 2005 which yielded a winning team were included in the analysis. The increase in matches won by Pakistan over India in the post-1986 period was statistically not significant. Changes in match performance against other frequently played nations, namely, increases against England and the West Indies as well as decreases against Australia and Sri Lanka, were larger than the one seen with India. Apparently, the Miandad effect neither generalized to all recurrently encountered opponents, nor was specific to India.

The covariate-adjusted frequency plot.

Count data arise in numerous fields of interest. Analysis of these data frequently require distributional assumptions. Although the graphical display of a fitted model is straightforward in the univariate scenario, this becomes more complex if covariate information needs to be included into the model. Stratification is one way to proceed, but has its limitations if the covariate has many levels or the number of covariates is large. The article suggests a marginal method which works even in the case that all possible covariate combinations are different (i.e. no covariate combination occurs more than once). For each covariate combination the fitted model value is computed and then summed over the entire data set. The technique is quite general and works with all count distributional models as well as with all forms of covariate modelling. The article provides illustrations of the method for various situations and also shows that the proposed estimator as well as the empirical count frequency are consistent with respect to the same parameter.

Suicide and general elections in Austria: do preceding regional suicide rate differentials foreshadow subsequent voting behavior swings?

BACKGROUND: Suicide-epidemiological research on short-term effects of elections on national/regional suicide and parasuicide incidence has yielded contradictory evidence. Reversing the cause-effect relationship of this line of research we investigated whether preceding regional suicide rates are related to subsequent election results. METHODS: For Austria's 121 districts, we regressed averaged standardized suicide rates for the preceding period (1988-1994) on political parties' subsequent electoral gains/losses (1999-to-1995) while controlling for a set of 12 domain-relevant psychosocial/economic indices. RESULTS: Stepwise weighted multiple regression led to a significant model. The 1999-to-1995 electoral gains/losses of two opposition parties, together with the population variation caused by migration balance and by births/deaths balance, accounted for a substantial part (30%) of the variability in preceding district-level suicide rates. Various other social indices failed to contribute further substantial increments to this model. CONCLUSIONS: This finding suggests that variations in preceding regional suicide incidence might be mirrored in subsequent changes in voting behavior. A speculative post hoc explanation for the finding is offered: on a community level, suicide's aftermath might produce socially and politically alienated survivors of suicide who co-shape swings towards opposition parties in subsequent general elections. The finding calls for more research on suicide's long-term aftermath. LIMITATIONS: Within-country replicability and cross-national generalizability await further investigation. At present, the factor/mechanism accounting for this finding is neither well-established nor has been directly tested.

Modeling data from water-level tasks: a test theoretical analysis.

The water-level tasks were invented by Piaget to diagnose the level of mental development of spatial abilities, especially behavior of liquids. It has become usual practice to dichotomise water-level responses by the subjects into right vs wrong using a certain tolerance limit (departure from the horizontal measured in degrees) and to fit a mixture of binomials to the raw scores resulting from a series of water-level tasks. The present study questions this procedure. Based on a series of 12 water-level tasks (round bottles at 12 different angles of orientation) presented to 431 subjects, both children and adults, females and males, the following results were obtained. First, considering the task difficulties (proportions of correct answers) and the scores, the effect of age was significant, but that for sex was not. Second, a mixture of binomials were shown to be inappropriate due to their ignoring the heterogeneity of the task difficulties, whereas latent class models, due to their taking this heterogeneity as well as that of the subjects into account, were successful in rendering a complete and well-rounded description of the data as observed for the eight water-level tasks showing bottles with orientations corresponding to 1, 2, 4, 5, 7, 8, 10, and 11 o'clock. Third, the Rasch model was valid as justification for the simple interpretation that subjects and tasks have a unidimensional scale in common with each other and that the raw score is the sufficient statistic for the subjects' performance. Fourth, employing the linear logistic test model, the task difficulty parameters according to the Rasch model could be attributed to a single parameter associated with the angle of inclination of the bottle. In all, the results do not give a final answer to the question of whether the concept of types (classes) or that of a continuous trait is the better of the two, but they do give rise to some warnings against the use of a mixture of binomials for modeling data on water-level tasks.

Variation in European suicide rates is better accounted for by latitude and longitude than by national percentage of Finno-Ugrians and Type O blood: a rebuttal of Lester and Kondrichin (2004).

The variation in contemporary suicide rates for men and women across 20 European nations is, in terms of shared variance, better accounted for by latitude and longitude than by national percentage of Finno-Ugrians and Type O blood, thus supporting the conclusion of Voracek, et al. in 2003 and refuting the supposition of Lester and Kondrichin of 2004. Discussion focuses on possible bases of this finding and on research problems pertaining to relations between suicide and blood type.

Parameter recovery and model selection in mixed Rasch models.

This study examines the precision of conditional maximum likelihood estimates and the quality of model selection methods based on information criteria (AIC and BIC) in mixed Rasch models. The design of the Monte Carlo simulation study included four test lengths (10, 15, 25, 40), three sample sizes (500, 1000, 2500), two simulated mixture conditions (one and two groups), and population homogeneity (equally sized subgroups) or heterogeneity (one subgroup three times larger than the other). The results show that both increasing sample size and increasing number of items lead to higher accuracy; medium-range parameters were estimated more precisely than extreme ones; and the accuracy was higher in homogeneous populations. The minimum-BIC method leads to almost perfect results and is more reliable than AIC-based model selection. The results are compared to findings by Li, Cohen, Kim, and Cho (2009) and practical guidelines are provided.

The Newcomb-Benford law in its relation to some common distributions.

An often reported, but nevertheless persistently striking observation, formalized as the Newcomb-Benford law (NBL), is that the frequencies with which the leading digits of numbers occur in a large variety of data are far away from being uniform. Most spectacular seems to be the fact that in many data the leading digit 1 occurs in nearly one third of all cases. Explanations for this uneven distribution of the leading digits were, among others, scale- and base-invariance. Little attention, however, found the interrelation between the distribution of the significant digits and the distribution of the observed variable. It is shown here by simulation that long right-tailed distributions of a random variable are compatible with the NBL, and that for distributions of the ratio of two random variables the fit generally improves. Distributions not putting most mass on small values of the random variable (e.g. symmetric distributions) fail to fit. Hence, the validity of the NBL needs the predominance of small values and, when thinking of real-world data, a majority of small entities. Analyses of data on stock prices, the areas and numbers of inhabitants of countries, and the starting page numbers of papers from a bibliography sustain this conclusion. In all, these findings may help to understand the mechanisms behind the NBL and the conditions needed for its validity. That this law is not only of scientific interest per se, but that, in addition, it has also substantial implications can be seen from those fields where it was suggested to be put into practice. These fields reach from the detection of irregularities in data (e.g. economic fraud) to optimizing the architecture of computers regarding number representation, storage, and round-off errors.

Pervasiveness of the IQ rise: a cross-temporal meta-analysis.

BACKGROUND: Generational IQ gains in the general population (termed the Flynn effect) show an erratic pattern across different nations as well as across different domains of intelligence (fluid vs crystallized). Gains of fluid intelligence in different countries have been subject to extensive research, but less attention was directed towards gains of crystallized intelligence, probably due to evidence from the Anglo-American sphere suggesting only slight gains on this measure. In the present study, development of crystallized intelligence in the German speaking general population is assessed. METHODOLOGY/PRINCIPAL FINDINGS: To investigate whether IQ gains for crystallized intelligence are in progress in German-speaking countries, two independent meta-analyses were performed. By means of a cited reference search in ISI Web of Science, all studies citing test manuals and review articles of two widely-used salient measures of crystallized intelligence were obtained. Additionally, the electronic database for German academic theses was searched to identify unpublished studies employing these tests. All studies reporting participants mean IQ or raw scores of at least one of the two measures were included in the present analyses, yielding over 500 studies (>1,000 samples; >45,000 individuals). We found a significant positive association between years of test performance and intelligence (1971-2007) amounting to about 3.5 IQ points per decade. CONCLUSIONS/SIGNIFICANCE: This study clearly demonstrates that crystallized IQ gains are substantial and of comparable strength as Flynn effects typically observed for measures of fluid intelligence in Central Europe. Since mean IQ was assessed in a large number of small, non-representative samples, our evidence suggests a remarkable robustness of these gains. Moreover, in both meta-analyses strength of gains was virtually identical. On the whole, results of the present study demonstrate a pervasive and generalizing Flynn effect in German-speaking countries.

Estimating the proportion of studies missing for meta-analysis due to publication bias.

OBJECTIVE: A potential problem with meta-analysis concerns missing studies due to publication bias. This paper focuses on one subtype of publication bias, namely selection bias (studies with unfavorable outcomes tend to be suppressed), wherein the main interest is in determining the proportion of unpublished studies. METHODS: As in the well-known trim and fill method, the key assumption is that studies with quantitative outcomes extremely unfavorable for the treatment are not published. Along with the assumption of a normal distribution for the complete set of published and unpublished studies, the proportion of unpublished studies is estimated by the degree of truncation from a left-truncated normal distribution. In addition, the mean and variance of this distribution are obtained in order to provide useful information regarding the mean effect of a treatment vs. a control, and the variance of this effect when controlling for truncation. The degree of truncation can be considered under two hypotheses: the true mean equals the estimated mean or the true mean is equal to zero. RESULTS: The uncorrected degree of truncation was found to be overestimated, but this bias was reduced when correcting for chance truncation. To incorporate additional information, weighted analysis was proposed. Instead of unweighted mean and variance of the published outcomes, their weighted analogues were used for analysis, with the weights expressing varying credibility across studies entering the meta-analysis. One hypothetical and three empirical examples illustrated the approach. CONCLUSION: The new method is very simple and its results are comparable to other meta-analytic methods. However, in contrast to existing methods, it can be applied to the study-specific outcomes alone.

Health-related quality of life in Austrian elementary school children.

BACKGROUND: Health-related quality of life (HRQL) is frequently used as an outcome criterion to evaluate the quality and effect of different therapies. However, little is known about the HRQL of the general population, the prevalence of specific HRQL problems and about which factors have an impact on HRQL assessments. OBJECTIVE: To examine children's HRQL from their own and their parents' perspectives. The study sample consisted of children attending the third and fourth grades of elementary school in the capital of Austria, Europe. METHODS: One thousand four hundred twelve children and 1185 parents completed child- and parent-versions of the Pediatric Quality of Life Inventorytrade mark (PedsQLtrade mark). In addition to the PedsQL questions, children and parents were asked a number of questions with regard to sociodemographic information and specific problems that were hypothesized to be associated with the children's HRQL. RESULTS: Altogether, the children demonstrated a good HRQL and their PedsQL scores were similar to those of children from other developed countries. About 15% of children showed a notably low HRQL, and two-thirds of these children were from financially less privileged families. Multivariate regression analyses identified the following factors associated with the children's HRQL: the family's perceived financial situation, parents' quality of life, children's school performance, medical and/or psychologic problems (eg, dyslexia, recurrent stomachache or headaches), chronic disease, a recent life-event (eg, divorce/separation of parents), and parents' satisfaction with school. CONCLUSIONS: Assessing children's HRQL may be helpful to take preventive action and to identify those who are in urgent need of special services.

Mixture analysis of longitudinal binary data.

The dependence of longitudinal binary outcomes on covariates and the covariation observed between them is often modelled by (multivariate) logistic and probit models, respectively, assuming specified association structure or random effects. Alternatively, latent class models may be used that capture the covariation by assuming heterogeneity of the observational units regarding their reaction tendencies while postulating independence within classes. In the presence of a few categorical covariates, the multi-group method of latent class analysis allows one to relate the class sizes and the class-specific response probabilities to these covariates. Wheeze data from the Harvard Six-Cities study on respiratory health are a typical example for such a situation: at four occasions, the wheeze status of 537 children was examined, 187 among them exposed to maternal smoking and 350 not exposed. Thus, there is a single binary covariate (maternal smoking versus no maternal smoking) making easily applicable the multi-group method of latent class analysis. Based on a series of unrestricted and restricted models having up to three classes for the exposed and not-exposed subgroup each, no statistically significant effect of maternal smoking on children's wheeze status could be substantiated. Moreover, it was not possible to show statistically significant difference at all between the two distributions of wheeze patterns collected from exposed and not-exposed children.

Latent class model diagnosis from a frequentist point of view.

This is in response to Garrett and Zeger (2000, Biometrics 56, 1055-1067) who, within the Bayesian framework, developed mainly graphical methods for latent class model diagnosis. Possible problems with this approach, and with its application to both generated and empirical data, are pointed out. The impact of the proposed tools cannot be understood by their reader, as no comparisons are made to results obtainable using established methods for latent class model diagnosis; this applies especially to overall goodness-of-fit tests, for which alternatives (bootstrap, Rudas-Clogg-Lindsay index of fit) are mentioned. Further, in one case of generated data, the methods proposed by Garrett and Zeger seem to give problematic results as to identifiability; in the case of the empirical data on major depression, they lead to accepting a suboptimal three-class model. In the latter case, one can be rather sure that an identifiable, well-fitting latent class model could have been identified--if Garrett and Zeger had also considered restricted latent class models.

Maternal bonding behaviour in schizophrenia and schizoaffective disorder, considering premorbid personality traits.

OBJECTIVE: Bonding between mother and child is described as a complex two-way process ensuring the needs of the child for nurture and protection. As such, it is dependent on the contribution of mother and child [1-3] whereby characteristics of personality of the child may have consequences on maternal bonding behaviour. In the current study the perception of maternal behaviour, premorbid personality traits and relationships between maternal behaviour and personality traits were investigated in schizophrenic and schizoaffective patients and their same-sex, healthy siblings. METHODS: We recruited 36 schizophrenic and schizoaffective patients and their same-sex healthy siblings. Information about maternal bonding behaviour was assessed by the Parental Bonding Instrument, information about premorbid personality traits was obtained from their mothers using the "Giessen-Test". RESULTS: Compared to their siblings, patients showed less social resonance, more permeability, less social competence and a more depressed and anxious mood. Furthermore, patients described their mothers to be less caring and to be more overprotective than their siblings described them. But there were strong associations between maternal bonding behaviour and premorbid personality traits. These findings were supported by missing significant differences in maternal care behaviour between patients and siblings when using premorbid characteristics as covariates. Significant high maternal overprotection perceived by patients with schizophrenia and schizoaffective disorders still remained after correcting for the influence of premorbid personality traits. CONCLUSION: The results suggest that premorbid personality traits should be considered not only in analyses of maternal care behaviour in schizophrenic and schizoaffective patients but also when studying other psychiatric patient groups.