Growth curves with explanatory variables and estimation of the effect of tagging

The von Bertalanffy growth model is extended to incorporate explanatory variables. The generalized model includes the switched growth model and the seasonal growth model as special cases, and can also be used to assess the tagging effect on growth. Distribution-free and consistent estimating functions are constructed for estimation of growth parameters from tag-recapture data in which age at release is unknown. This generalizes the work of James (1991, Biometrics 47 1519-1530) who considered the classical model and allowed for individual variability in growth. A real dataset from barramundi (Lates calcarifer) is analysed to estimate the growth parameters and possible effect of tagging on growth.

Growth curves with time-dependent explanatory variables

A class of growth models incorporating time-dependent factors and stochastic perturbations are introduced. The proposed model includes the existing growth models used in fisheries as special cases. Particular attention is given to growth of a population (in average weight or length) from which observations are taken randomly each time and the analysis of tag-recapture data. Two real data sets are used for illustration: (a) to estimate the seasonal effect and population density effect on growth of farmed prawn (Penaeus monodon) from weight data and (b) to assess the effect of tagging on growth of barramundi (Lates calcarifer)

Evolution over time of heavy vehicle volume in toll roads: A dynamic panel data to identify key explanatory variables in Spain

Improving the knowledge of demand evolution over time is a key aspect in the evaluation of transport policies and in forecasting future investment needs. It becomes even more critical for the case of toll roads, which in recent decades has become an increasingly common device to fund road projects. However, literature regarding demand elasticity estimates in toll roads is sparse and leaves some important aspects to be analyzed in greater detail. In particular, previous research on traffic analysis does not often disaggregate heavy vehicle demand from the total volume, so that the specific behavioral patternsof this traffic segment are not taken into account. Furthermore, GDP is the main socioeconomic variable most commonly chosen to explain road freight traffic growth over time. This paper seeks to determine the variables that better explain the evolution of heavy vehicle demand in toll roads over time. To that end, we present a dynamic panel data methodology aimed at identifying the key socioeconomic variables that explain the behavior of road freight traffic throughout the years. The results show that, despite the usual practice, GDP may not constitute a suitable explanatory variable for heavy vehicle demand. Rather, considering only the GDP of those sectors with a high impact on transport demand, such as construction or industry, leads to more consistent results. The methodology is applied to Spanish toll roads for the 1990?2011 period. This is an interesting case in the international context, as road freight demand has experienced an even greater reduction in Spain than elsewhere, since the beginning of the economic crisis in 2008.

State inspection program evaluation and data analysis: data base E SPSS frequencies tabulations for brake components and explanatory variables. Volume III. Final report.

National Highway Traffic Safety Administration, Office of Vehicle Safety Research, Washington, D.C.

The detection of interaction effects ; a report on a computer program for the selection of optimal combinations of explanatory variables /

Errata sheet inserted.

Dimension Reduction of the Explanatory Variables in Multiple Linear Regression

2002 Mathematics Subject Classification: 62J05, 62G35.

Methods of Regularities Searching Based on Optimal Partitioning

The purpose of discussed optimal valid partitioning (OVP) methods is uncovering of ordinal or continuous explanatory variables effect on outcome variables of different types. The OVP approach is based on searching partitions of explanatory variables space that in the best way separate observations with different levels of outcomes. Partitions of single variables ranges or two-dimensional admissible areas for pairs of variables are searched inside corresponding families. Statistical validity associated with revealed regularities is estimated with the help of permutation test repeating search of optimal partition for each permuted dataset. Method for output regularities selection is discussed that is based on validity evaluating with the help of two types of permutation tests.

Buffel grass in Queensland's semi-arid woodlands: response to local and landscape scale variables, and relationship with grass, forb and reptile species.

Buffel grass [Pennisetum ciliare (L.) Link] has been widely introduced in the Australian rangelands as a consequence of its value for productive grazing, but tends to competitively establish in non-target areas such as remnant vegetation. In this study, we examined the influence landscape-scale and local-scale variables had upon the distribution of buffel grass in remnant poplar box (Eucalyptus populnea F. Muell.) dominant woodland fragments in the Brigalow Bioregion, Queensland. Buffel grass and variables thought to influence its distribution in the region were measured at 60 sites, which were selected based on the amount of native woodland retained in the landscape and patch size. An information-theoretic modelling approach and hierarchical partitioning revealed that the most influential variable was the percent of retained vegetation within a 1-km spatial extent. From this, we identified a critical threshold of similar to 30% retained vegetation in the landscape, above which the model predicted buffel grass was not likely to occur in a woodland fragment. Other explanatory variables in the model were site based, and included litter cover and long-term rainfall. Given the paucity of information on the effect of buffel grass upon biodiversity values, we undertook exploratory analyses to determine whether buffel grass cover influenced the distribution of grass, forb and reptile species. We detected some trends; hierarchical partitioning revealed that buffel grass cover was the most important explanatory variable describing habitat preferences of four reptile species. However, establishing causal links - particularly between native grass and forb species and buffel grass - was problematic owing to possible confounding with grazing pressure. We conclude with a set of management recommendations aimed at reducing the spread of buffel grass into remnant woodlands.

The effect of ownership structure, country governance, and financial development on the capital structure of unlisted eastern European firms

This paper investigates the determinants of capital structure for a sample of 20,713 unlisted firms from 11 eastern European countries over the period 1994-2004. We employ usual firm-specific financial variables as well as country-specific variables that describe the degrees of governance structure and financial development of each country. Using regression analysis, our results indicate that firm ownership concentration and country governance structure are insignificant explanatory variables to the degree of leverage of the firms in our sample. On the other hand, indicators of country financial development are robust determinants of capital structure. However, the marginal explanatory power of country-specific variables is small. We conclude that firm-specific characteristics are decisive in capital structure.

Combined effect of anterior malocclusion and inadequate lip coverage on dental trauma in primary teeth

Objectives: The main objective of this study was to investigate whether the interaction of malocclusion (open bite or increased overjet) combined with inadequate lip coverage strengthens its association with traumatic dental injury (TDI) in the primary teeth of preschool children compared to the presence of malocclusion alone. Subjects and methods: A cross-sectional survey was conducted with 376 children aged 3659 months who attended the National Day of Childrens Vaccination. Presence of TDI, tooth discoloration, and sinus tract were evaluated in the children. Variables associated with occlusion were also evaluated. A Poisson regression analysis was performed to verify the association between the explanatory variables and TDI as well as possible interactions among the variables. Then, the prevalence ratio was calculated. Results: The prevalence of TDI was 27.7%. The maxillary central incisor was the most affected tooth, without differences between the right and left sides. Boys had more dental trauma than girls (P = 0.04). The most common TDI was crown fracture restricted to the enamel (58.4%). Children with a combination of anterior open bite or increased overjet and inadequate lip coverage presented a higher prevalence of TDI than when the malocclusions were presented alone (P < 0.05). The same trends were observed when we included, in the final adjusted model, increased overjet instead of open bite. Conclusions: Anterior malocclusions of primary teeth such as increased overjet and anterior open bite are statistically significantly associated with dental trauma only when inadequate lip coverage is also present.

Degree of multicollinearity and variables involved in linear dependence in additive-dominant models

The objective of this work was to assess the degree of multicollinearity and to identify the variables involved in linear dependence relations in additive-dominant models. Data of birth weight (n=141,567), yearling weight (n=58,124), and scrotal circumference (n=20,371) of Montana Tropical composite cattle were used. Diagnosis of multicollinearity was based on the variance inflation factor (VIF) and on the evaluation of the condition indexes and eigenvalues from the correlation matrix among explanatory variables. The first model studied (RM) included the fixed effect of dam age class at calving and the covariates associated to the direct and maternal additive and non-additive effects. The second model (R) included all the effects of the RM model except the maternal additive effects. Multicollinearity was detected in both models for all traits considered, with VIF values of 1.03 - 70.20 for RM and 1.03 - 60.70 for R. Collinearity increased with the increase of variables in the model and the decrease in the number of observations, and it was classified as weak, with condition index values between 10.00 and 26.77. In general, the variables associated with additive and non-additive effects were involved in multicollinearity, partially due to the natural connection between these covariables as fractions of the biological types in breed composition.

Moderating effect of allocentrism on the pay referent comparison-pay level satisfaction relationship

Pay referent comparisons (comparisons of one's salary to that of others) such as other-inside (salary of other people in the organisation), other-outside (the market rate), and cost-of- living, have been shown to influence pay level satisfaction. Bordia and Blau (1998) identified family as another referent that had a significant effect on pay level satisfaction in a sample of public and private sector employees in India. The finding was interpreted in view of the importance of family in collectivistic cultures. In the study reported here, the moderating influence of an individual differences variable, allocentrism-idiocentrism (the individual level conceptualisation of collectivism-individualism) on pay referent comparison-pay level satisfaction relationship was investigated. A sample of 146 employees from three public sector organisations in India participated in the study. In line with the predictions, results showed that after controlling for age, tenure, and pay level, pay referent comparisons explained more variance in pay level satisfaction for allocentrics than for idiocentrics. Family and pay level were stronger explanatory variables of pay level satisfaction for allocentrics and idiocentrics, respectively, while cost of living was a significant explanatory variable for both sub-groups.

EFFECT OF FARMING PRACTICES AND FARM HISTORY ON INCIDENCE OF COCONUT LETHAL YELLOWING IN MOZAMBIQUE

Management of coconut ( Cocos nucifera ) lethal yellowing disease (CLYD), which has killed about eight million coconut trees in Mozambique, has proved challenging. The objective of this study was to investigate the impact of farming practices and related history, on the CLYD incidence in Mozambique. The methodology included a socioeconomic questionnaire to the households and direct observations on the palm farms. The collected data were analysed using logistic regression. Five out of 11 explanatory variables tested, namely farm age, availability of other palm species on the coconut farm, type of coconut varieties grown, root cut practices, and intercropping had a significant (P< 0.05) effect on CLYD incidence. Coconut farms <10 years had higher odds of higher disease incidence compared to the farms between 10 to 40 years old. The presence of other palm species in the coconut farms had two times higher odds of having higher disease incidence levels compared to farms without other palm species. Tall coconut varieties were likely to be more tolerant to CLYD compared to dwarf varieties. Coconut farms with some kind of intercropping had two times higher odds of having higher disease incidence levels compared to pure stands. The practice of cutting coconut roots had three times higher odds of having high disease incidence levels compared to non-practicing farms. Farm age, availability of other palm species on the coconut farm, type of coconut varieties grown, root cut practices and intercropping need to be considered for integrated CLYD management.

Does psychological stress mediate social deprivation in tooth loss?

It is unclear which theoretical dimension of psychological stress affects health status. We hypothesized that both distress and coping mediate the relationship between socio-economic position and tooth loss. Cross-sectional data from 2915 middle-aged adults evaluated retention of < 20 teeth, behaviors, psychological stress, and sociodemographic characteristics. Principal components analysis of the Perceived Stress Scale (PSS) extracted 'distress' (a = 0.85) and 'coping' (a =0.83) factors, consistent with theory. Hierarchical entry of explanatory variables into age- and sex-adjusted logistic regression models estimated odds ratios (OR) and 95% confidence intervals [95% CI] for retention of < 20 teeth. Analysis of the separate contributions of distress and coping revealed a significant main effect of coping (OR = 0.7 [95% CI = 0.7-0.8]), but no effect for distress (OR = 1.0 [95% CI = 0.9-1.1]) or for the interaction of coping and distress. Behavior and psychological stress only modestly attenuated socio-economic inequality in retention of < 20 teeth, providing evidence to support a mediating role of coping.