Selecting candidate predictor variables for the modelling of post-discharge mortality from sepsis: a protocol development project.

Background: Post-discharge mortality is a frequent but poorly recognized contributor to child mortality in resource limited countries. The identification of children at high risk for post-discharge mortality is a critically important first step in addressing this problem. Objectives: The objective of this project was to determine the variables most likely to be associated with post-discharge mortality which are to be included in a prediction modelling study. Methods: A two-round modified Delphi process was completed for the review of a priori selected variables and selection of new variables. Variables were evaluated on relevance according to (1) prediction (2) availability (3) cost and (4) time required for measurement. Participants included experts in a variety of relevant fields. Results: During the first round of the modified Delphi process, 23 experts evaluated 17 variables. Forty further variables were suggested and were reviewed during the second round by 12 experts. During the second round 16 additional variables were evaluated. Thirty unique variables were compiled for use in the prediction modelling study. Conclusion: A systematic approach was utilized to generate an optimal list of candidate predictor variables for the incorporation into a study on prediction of pediatric post-discharge mortality in a resource poor setting.

Cooperative conflict-solving during adolescence : relationships with cognitive-behavioural and predictor variables. 'Resolución de conflictos cooperativa durante la adolescencia : relaciones con variables cognitivo-conductuales y predictores'.

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Using Trauma Injury Severity Score (TRISS) variables to predict length of hospital stay following trauma in New Zealand

Aim – To develop and assess the predictive capabilities of a statistical model that relates routinely collected Trauma Injury Severity Score (TRISS) variables to length of hospital stay (LOS) in survivors of traumatic injury. Method – Retrospective cohort study of adults who sustained a serious traumatic injury, and who survived until discharge from Auckland City, Middlemore, Waikato, or North Shore Hospitals between 2002 and 2006. Cubic-root transformed LOS was analysed using two-level mixed-effects regression models. Results – 1498 eligible patients were identified, 1446 (97%) injured from a blunt mechanism and 52 (3%) from a penetrating mechanism. For blunt mechanism trauma, 1096 (76%) were male, average age was 37 years (range: 15-94 years), and LOS and TRISS score information was available for 1362 patients. Spearman’s correlation and the median absolute prediction error between LOS and the original TRISS model was ρ=0.31 and 10.8 days, respectively, and between LOS and the final multivariable two-level mixed-effects regression model was ρ=0.38 and 6.0 days, respectively. Insufficient data were available for the analysis of penetrating mechanism models. Conclusions – Neither the original TRISS model nor the refined model has sufficient ability to accurately or reliably predict LOS. Additional predictor variables for LOS and other indicators for morbidity need to be considered.

Dynamics between patent latent variables and patent price

This paper focuses on studying the relationship between patent latent variables and patent price. From the existing literature, seven patent latent variables, namely age, generality, originality, foreign filings, technology field, forward citations, and backward citations were identified as having an influence on patent value. We used Ocean Tomo's patent auction price data in this study. We transformed the price and the predictor variables (excluding the dummy variables) to its logarithmic value. The OLS estimates revealed that forward citations and foreign filings were positively correlated to price. Both the variables jointly explained 14.79% of the variance in patent pricing. We did not find sufficient evidence to come up with any definite conclusions on the relationship between price and the variables such as age, technology field, generality, backward citations and originality. The Heckman two-stage sample selection model was used to test for selection bias. (C) 2011 Elsevier Ltd. All rights reserved.

Proposal and validation of methodologies for the categorisation of continuous variables in the development of prediction models

158 p.

On Regression Methods for Virtual Metrology in Semiconductor Manufacturing

Virtual metrology (VM) aims to predict metrology values using sensor data from production equipment and physical metrology values of preceding samples. VM is a promising technology for the semiconductor manufacturing industry as it can reduce the frequency of in-line metrology operations and provide supportive information for other operations such as fault detection, predictive maintenance and run-to-run control. The prediction models for VM can be from a large variety of linear and nonlinear regression methods and the selection of a proper regression method for a specific VM problem is not straightforward, especially when the candidate predictor set is of high dimension, correlated and noisy. Using process data from a benchmark semiconductor manufacturing process, this paper evaluates the performance of four typical regression methods for VM: multiple linear regression (MLR), least absolute shrinkage and selection operator (LASSO), neural networks (NN) and Gaussian process regression (GPR). It is observed that GPR performs the best among the four methods and that, remarkably, the performance of linear regression approaches that of GPR as the subset of selected input variables is increased. The observed competitiveness of high-dimensional linear regression models, which does not hold true in general, is explained in the context of extreme learning machines and functional link neural networks.

Signal propagation in Bayesian networks and its relationship with intrinsically multivariate predictive variables

A set of predictor variables is said to be intrinsically multivariate predictive (IMP) for a target variable if all properly contained subsets of the predictor set are poor predictors of the. target but the full set predicts the target with great accuracy. In a previous article, the main properties of IMP Boolean variables have been analytically described, including the introduction of the IMP score, a metric based on the coefficient of determination (CoD) as a measure of predictiveness with respect to the target variable. It was shown that the IMP score depends on four main properties: logic of connection, predictive power, covariance between predictors and marginal predictor probabilities (biases). This paper extends that work to a broader context, in an attempt to characterize properties of discrete Bayesian networks that contribute to the presence of variables (network nodes) with high IMP scores. We have found that there is a relationship between the IMP score of a node and its territory size, i.e., its position along a pathway with one source: nodes far from the source display larger IMP scores than those closer to the source, and longer pathways display larger maximum IMP scores. This appears to be a consequence of the fact that nodes with small territory have larger probability of having highly covariate predictors, which leads to smaller IMP scores. In addition, a larger number of XOR and NXOR predictive logic relationships has positive influence over the maximum IMP score found in the pathway. This work presents analytical results based on a simple structure network and an analysis involving random networks constructed by computational simulations. Finally, results from a real Bayesian network application are provided. (C) 2012 Elsevier Inc. All rights reserved.

Ball possession effectiveness in men's and women's elite basketball according to situational variables in different game periods

The aim of the present study was to identify the importance of floorball tactical variables to predict ball possession effectiveness, when controlling quality of opposition and game periods. The sample was composed by 1500 ball possessions, corresponding to 14 games randomly selected from the International Championships played during 2008 and 2010 (World Championship, Four nations tournament and classificatory phases for World Championship) by teams from different competition levels (HIGH, INTERMEDIATE and LOW). The effects of the predictor variables on successful ball possessions according to the three game contexts (HIGH vs. HIGH; HIGH vs. LOW; LOW vs. LOW games) were analyzed using Binomial Logistic Regressions. The results showed no interaction with the game period. In HIGH vs. HIGH games, quality of opposition showed an association with ball possession effectiveness with ending zone, offensive system, possession duration, height of shooting and defensive pressures previous to the shot. In HIGH vs. LOW games the important factors were the starting zone, possession duration, defensive pressure previous to the last pass and to the shot, technique of shooting and the number players involved in each ball possession. Finally, in LOW vs. LOW games, the results emphasized the importance of starting and ending zones, the number of passes used and the technique of shooting. In conclusion, elite floorball performance is mainly affected by quality of opposition showing different game patterns in each context that should be considered by coaches when preparing practices and competitions.

Dimension Reduction of the Explanatory Variables in Multiple Linear Regression

2002 Mathematics Subject Classification: 62J05, 62G35.

Psychosocial variables associated with the co-occurrence of risky sexual behavior with alcohol consumption among university students

This study examined the association of theoretically guided and empirically identified psychosocial variables on the co-occurrence of risky sexual behavior with alcohol consumption among university students. The study utilized event analysis to determine whether risky sex occurred during the same event in which alcohol was consumed. Relevant conceptualizations included alcohol disinhibition, self-efficacy, and social network theories. Predictor variables included negative condom attitudes, general risk taking, drinking motives, mistrust, social group membership, and gender. Factor analysis was employed to identify dimensions of drinking motives. Measured risky sex behaviors were (a) sex without a condom, (b) sex with people not known very well, (c) sex with injecting drug users (IDUs), (d) sex with people without knowing whether they had a STD, and (e) sex with using drugs. A purposive sample was used and included 222 male and female students recruited from a major urban university. Chi-square analysis was used to determine whether participants were more likely to engage in risky sex behavior in different alcohol use contexts. These contexts were only when drinking, only when not drinking, and when drinking or not. The chi-square findings did not support the hypothesis that university students who use alcohol with sex will engage in riskier sex. These results added to the literature by extending other similar findings to a university student sample. For each of the observed risky sex behaviors, discriminant analysis methodology was used to determine whether the predictor variables would differentiate the drinking contexts, or whether the behavior occurred. Results from discriminant analyses indicated that sex with people not known very well was the only behavior for which there were significant discriminant functions. Gender and enhancement drinking motives were important constructs in the classification model. Limitations of the study and implications for future research, social work practice and policy are discussed. ^

Psychosocial variables associated with the co-occurance of risky sexual behavior with alcohol consumption among university students

This study examined the association of theoretically guided and empirically identified psychosocial variables on the co-occurrence of risky sexual behavior with alcohol consumption among university students. The study utilized event analysis to determine whether risky sex occurred during the same event in which alcohol was consumed. Relevant conceptualizations included alcohol disinhibition, self-efficacy, and social network theories. Predictor variables included negative condom attitudes, general risk taking, drinking motives, mistrust, social group membership, and gender. Factor analysis was employed to identify dimensions of drinking motives. Measured risky sex behaviors were (a) sex without a condom, (b) sex with people not known very well, (c) sex with injecting drug users (IDUs), (d) sex with people without knowing whether they had a STD, and (e) sex with using drugs. A purposive sample was used and included 222 male and female students recruited from a major urban university. Chi-square analysis was used to determine whether participants were more likely to engage in risky sex behavior in different alcohol use contexts. These contexts were only when drinking, only when not drinking, and when drinking or not. The chi-square findings did not support the hypothesis that university students who use alcohol with sex will engage in riskier sex. These results added to the literature by extending other similar findings to a university student sample. For each of the observed risky sex behaviors, discriminant analysis methodology was used to determine whether the predictor variables would differentiate the drinking contexts, or whether the behavior occurred. Results from discriminant analyses indicated that sex with people not known very well was the only behavior for which there were significant discriminant functions. Gender and enhancement drinking motives were important constructs in the classification model. Limitations of the study and implications for future research, social work practice and policy are discussed.

Women's disengagement from legal proceedings for intimate partner violence: sociodemographic and psychological variables

The aim of this study is to shed light on what makes women decide whether or not to continue with legal proceedings for intimate partner violence once they have commenced. Legal professionals, members of the police force, and women in Spain were interviewed to help draft a questionnaire that was applied to a sample of 345 women who had undertaken legal proceedings against their (ex)partners. Socio-demographic, emotional, and psychological variables were considered as possible predictor variables and included in a logistic regression analysis. Results show that the best equation for predicting disengagement from legal procedures includes the level of support received by the victim, contact with the aggressor, thoughts about going back with the aggressor, and a feeling of guilt. The essential role of the psychological support during the legal process is emphasized in conclusions.

Teacher-child relationship quality for young children with parent reported language concerns

Previous research has demonstrated the importance of the qualities of the teacher-child relationship on children’s development. Close teacher-child relationships are especially important for children at risk. Positive relationships have been shown to have beneficial effects on children’s social and academic development (Birch & Ladd, 1997; Pianta & Stuhlman, 2004). Children with language difficulties are likely to face increased risks with regard to long term social and academic outcomes. The purpose of the current research was to gain greater understanding of the qualities of teacher-child relationships for young children with parent reported language concerns. The research analyses completed for this thesis involved the use of data from the public-access database of Growing Up in Australia: The Longitudinal Study of Australian Children (LSAC). LSAC is a longitudinal study involving a nationally representative sample of 10,000 Australian children. Data are being collected biennially from 2004 (Wave 1 data collection) until 2010 (Wave 4 data collection). LSAC has a cross-sequential research design involving two cohorts, an infant cohort (0-1 year at age of recruitment) and a kindergarten cohort (4-5 years at age of recruitment). Two studies are reported in this thesis using data for the LSAC Kindergarten Cohort which had 4983 child participants at recruitment. Study 1 used Wave 1 data to identify the differences between teacher-child relationship qualities for children with parent reported language concerns and their peers. Children identified by parents for whom concerns were held about their receptive and expressive language, as measured by items from the Parents’ Evaluation of Developmental Status (PEDS) (Glascoe, 2000) were the target (at risk) group in the study (n = 210). A matched case control group of peers (n = 210), matched on the child characteristics of sex, age, cultural and linguistic differences (CALD), and socio-economic positioning (SEP), were the comparison group for this analysis. Teacher-child relationship quality was measured by teacher reports on the Closeness and Conflict scales from the short version of the Student-Teacher Relationship Scale (STRS) (Pianta, 2001). There were statistically significant differences in the levels of closeness and conflict between the two groups. The target group had relationships with their teachers that had lower levels of closeness and higher levels of conflict than the control group. Study 2 reports analyses that examined the stability of the qualities of the teacher-child relationships at Wave 1 (4-5 years) and the qualities of the teacher-child relationships at Wave 2 (6-7 years). This time frame crosses the period of the children’s transition to school. The study examined whether early patterns in the qualities of the teacher-child relationship for children with parent reported language concerns at Wave 1 predicted the qualities of the teacher-child relationship outcomes in the early years of formal school. The sample for this study consisted of the group of children identified with PEDS language concerns at Wave 1 who also had teacher report data at Wave 2 (n = 145). Teacher-child relationship quality at Wave 1 and Wave 2 was again measured by the STRS scales of Closeness and Conflict. Results from multiple regression models indicated that teacher-child relationship quality at Wave 1 significantly contributed to the prediction of the quality of the teacher-child relationship at Wave 2, beyond other predictor variables included in the regression models. Specifically, Wave 1 STRS Closeness scores were the most significant predictor for STRS Closeness scores at Wave 2, while Wave 1 STRS Conflict scores were the only significant predictor for Wave 2 STRS Conflict outcomes. These results indicate that the qualities of the teacher-child relationship experienced prior to school by children with parent reported language concerns remained stable across transitions into formal schooling at which time the child had a different teacher. The results of these studies provide valuable insight into the nature of teacher-child relationship quality for young children with parent reported language concerns. These children experienced teacher-child relationships of a lower quality when compared with peers and, additionally, the qualities of these relationships prior to formal schooling were predictive of the qualities of the relationships in the early years of formal schooling. This raises concerns, given the increased risks of poorer social and academic outcomes already faced by children with language difficulties, that these early teacher-child relationships have an impact on future teacher-child relationships. Results of these studies are discussed with these considerations in mind and also discussed in terms of the implications for educational theory, policy and practice.

The reliability and validity of the Severity of Dependence Scale for detecting cannabis dependence in psychosis.

Aims: To determine the reliability and validity of the Severity of Dependence Scale (SDS) for detecting cannabis dependence in a large sample of in-patients with a schizophrenia spectrum disorder. Design: Cross-sectional study. Participants: Participants were 153 in-patients with a schizophrenia spectrum disorder in Brisbane, Australia. Measurements: Participants were administered the SDS for cannabis dependence in the past 12 months. The presence of Diagnostic and Statistical Manual Version-IV (DSM-IV) cannabis dependence in the previous 12 months was assessed using the Comprehensive International Diagnostic Interview (CIDI). Findings: The SDS had high levels of internal consistency and strong construct and concurrent validity. Individuals with a score of ≥2 on the SDS were nearly 30 times more likely to have DSM-IV cannabis dependence. The SDS was the strongest predictor of DSM-IV cannabis dependence after controlling for other predictor variables. Conclusions: The SDS is a brief, valid and reliable screen for cannabis dependence among people with psychosis