New validated prognostic models and prognostic calculators in patients with low-grade gliomas diagnosed by central pathology review: a pooled analysis of EORTC/RTOG/NCCTG phase III clinical trials.

Background In a previous study, the European Organisation for Research and Treatment of Cancer (EORTC) reported a scoring system to predict survival of patients with low-grade gliomas (LGGs). A major issue in the diagnosis of brain tumors is the lack of agreement among pathologists. New models in patients with LGGs diagnosed by central pathology review are needed. Methods Data from 339 EORTC patients with LGGs diagnosed by central pathology review were used to develop new prognostic models for progression-free survival (PFS) and overall survival (OS). Data from 450 patients with centrally diagnosed LGGs recruited into 2 large studies conducted by North American cooperative groups were used to validate the models. Results Both PFS and OS were negatively influenced by the presence of baseline neurological deficits, a shorter time since first symptoms (<30 wk), an astrocytic tumor type, and tumors larger than 5 cm in diameter. Early irradiation improved PFS but not OS. Three risk groups have been identified (low, intermediate, and high) and validated. Conclusions We have developed new prognostic models in a more homogeneous LGG population diagnosed by central pathology review. This population better fits with modern practice, where patients are enrolled in clinical trials based on central or panel pathology review. We could validate the models in a large, external, and independent dataset. The models can divide LGG patients into 3 risk groups and provide reliable individual survival predictions. Inclusion of other clinical and molecular factors might still improve models' predictions.

Fading models and metrics for contemporary wireless systems

The purpose of this paper is to examine (1) some of the models commonly used to represent fading,and (2) the information-theoretic metrics most commonly used to evaluate performance over those models. We raise the question of whether these models and metrics remain adequate in light of the advances that wireless systems haveundergone over the last two decades. Weaknesses are pointedout, and ideas on possible fixes are put forth.

Rates of cultural change and patterns of cultural accumulation in stochastic models of social transmission.

Cultural variation in a population is affected by the rate of occurrence of cultural innovations, whether such innovations are preferred or eschewed, how they are transmitted between individuals in the population, and the size of the population. An innovation, such as a modification in an attribute of a handaxe, may be lost or may become a property of all handaxes, which we call "fixation of the innovation." Alternatively, several innovations may attain appreciable frequencies, in which case properties of the frequency distribution-for example, of handaxe measurements-is important. Here we apply the Moran model from the stochastic theory of population genetics to study the evolution of cultural innovations. We obtain the probability that an initially rare innovation becomes fixed, and the expected time this takes. When variation in cultural traits is due to recurrent innovation, copy error, and sampling from generation to generation, we describe properties of this variation, such as the level of heterogeneity expected in the population. For all of these, we determine the effect of the mode of social transmission: conformist, where there is a tendency for each naïve newborn to copy the most popular variant; pro-novelty bias, where the newborn prefers a specific variant if it exists among those it samples; one-to-many transmission, where the variant one individual carries is copied by all newborns while that individual remains alive. We compare our findings with those predicted by prevailing theories for rates of cultural change and the distribution of cultural variation.

A-1 Monthly Public Assistance Statistical Report Family Investment Program, September 2005

Monthly Public Assistance Statistical Report Family Investment Program

Women's work histories in Italy: education as investment in reconciliation and legitimacy?

Within pre-enlargement Europe, Italy records one of the widest employment rate gaps between highly and poorly educated women, as well one of the largest differences in the share, among working women, of public sector employment. Building on these stylized facts and using the Longitudinal Survey of Italian Households (ILFI), we investigate the working trajectories of three cohorts of Italian women born between 1935 and 1964 and observed from their first job until they are in their forties. We use mainly, but not exclusively, event history analysis in order to identify the main factors that influence entry into and exit from paid work over the life course. Our results suggest that in the Italian context, where employment protection policies have also been used as surrogate measures to favour reconciliation between family and work, and where traditional gender norms still persist, education is so important for women's employment decisions because it represents an investment in 'reconciliation' and 'work legitimacy' over and above investment in human capital.

Swain: Stata module to correct the SEM chi-square overidentification test in small sample sizes or complex models. Statistical Software Components S457617, Boston College Department of Economics.

Swain corrects the chi-square overidentification test (i.e., likelihood ratio test of fit) for structural equation models whethr with or without latent variables. The chi-square statistic is asymptotically correct; however, it does not behave as expected in small samples and/or when the model is complex (cf. Herzog, Boomsma, & Reinecke, 2007). Thus, particularly in situations where the ratio of sample size (n) to the number of parameters estimated (p) is relatively small (i.e., the p to n ratio is large), the chi-square test will tend to overreject correctly specified models. To obtain a closer approximation to the distribution of the chi-square statistic, Swain (1975) developed a correction; this scaling factor, which converges to 1 asymptotically, is multiplied with the chi-square statistic. The correction better approximates the chi-square distribution resulting in more appropriate Type 1 reject error rates (see Herzog & Boomsma, 2009; Herzog, et al., 2007).

Children in the welfare state. A social investment approach

Children occupy centre-stage in any new welfare equilibrium. Failure to support families may produce either of two undesirable scenarios. We shall see a society without children if motherhood remains incompatible with work. A new family policy needs to recognize that children are a collective asset and that the cost of having children is rising. The double challenge is to eliminate the constraints on having children in the first place, and to ensure that the children we have are ensured optimal opportunities. The simple reason why a new social contract is called for is that fertility and child quality combine both private utility and societal gains. And like no other epoch in the past, the societal gains are mounting all-the-while that families’ ability to produce these social gains is weakening.In the following 1 analyze the twin challenges of fertility and child development. I then examine which kind of policy mix will ensure both the socially desired level of fertility and investment in our children? The task is to identify a Paretian optimum that will maximize efficiency gains and social equity simultaneously.

Political mobilisation and models of trade unionism : Southern Europe in comparative perspective

The relationship between union membership and political mobilization has been studied under many perspectives, but quantitative cross-national analyses have been hampered by the absence of international comparable survey data until the first round of the European Social Survey (ESS-2002) was made available. Using different national samples from this survey in four moments of time (2002, 2004 and 2006), our paper provides evidence of cross-country divergence in the empirical association between political mobilisation and trade union membership. Cross-national differences in union members’ political mobilization, we argue, can be explained by the existence of models of unionism that in turn differ with respect to two decisive factors: the institutionalisation of trade union activity and the opportunities left-wing parties have available for gaining access to executive power.

A-1 Monthly Public Assistance Statistical Report Family Investment Program, October 2005

A-1 Monthly Public Assistance Statistical Report Family Investment Program, October 2005

A-1 Monthly Public Assistance Statistical Report Family Investment Program, November 2005

A-1 - Monthly Public Assistance Statistical Report Family Investment Program - November 2005

A-1 Monthly Public Assistance Statistical Report-Family Investment Program, December 2005

A-1 December 2005 - Monthly Public Assistance Statistical Report - Family Investment Program

A-1 Monthly Public Assistance Statistical Report Family Investment Program, January 2006

Monthly Public Assistance Statistical Report Family Investment Program, January 2006

Generalized linear and generalized additive models in studies of species distributions: setting the scene

An important statistical development of the last 30 years has been the advance in regression analysis provided by generalized linear models (GLMs) and generalized additive models (GAMs). Here we introduce a series of papers prepared within the framework of an international workshop entitled: Advances in GLMs/GAMs modeling: from species distribution to environmental management, held in Riederalp, Switzerland, 6-11 August 2001.We first discuss some general uses of statistical models in ecology, as well as provide a short review of several key examples of the use of GLMs and GAMs in ecological modeling efforts. We next present an overview of GLMs and GAMs, and discuss some of their related statistics used for predictor selection, model diagnostics, and evaluation. Included is a discussion of several new approaches applicable to GLMs and GAMs, such as ridge regression, an alternative to stepwise selection of predictors, and methods for the identification of interactions by a combined use of regression trees and several other approaches. We close with an overview of the papers and how we feel they advance our understanding of their application to ecological modeling.

PACIC Instrument: disentangling dimensions using published validation models.

OBJECTIVE: To better understand the structure of the Patient Assessment of Chronic Illness Care (PACIC) instrument. More specifically to test all published validation models, using one single data set and appropriate statistical tools. DESIGN: Validation study using data from cross-sectional survey. PARTICIPANTS: A population-based sample of non-institutionalized adults with diabetes residing in Switzerland (canton of Vaud). MAIN OUTCOME MEASURE: French version of the 20-items PACIC instrument (5-point response scale). We conducted validation analyses using confirmatory factor analysis (CFA). The original five-dimension model and other published models were tested with three types of CFA: based on (i) a Pearson estimator of variance-covariance matrix, (ii) a polychoric correlation matrix and (iii) a likelihood estimation with a multinomial distribution for the manifest variables. All models were assessed using loadings and goodness-of-fit measures. RESULTS: The analytical sample included 406 patients. Mean age was 64.4 years and 59% were men. Median of item responses varied between 1 and 4 (range 1-5), and range of missing values was between 5.7 and 12.3%. Strong floor and ceiling effects were present. Even though loadings of the tested models were relatively high, the only model showing acceptable fit was the 11-item single-dimension model. PACIC was associated with the expected variables of the field. CONCLUSIONS: Our results showed that the model considering 11 items in a single dimension exhibited the best fit for our data. A single score, in complement to the consideration of single-item results, might be used instead of the five dimensions usually described.

A-1 Monthly Public Assistance Statistical Report-Family Investment Program, February 2006

A-1 Monthly Public Assistance Statistical Report Family Investment Program, February 2006