Prison Return Rate Down-Again, Data Download, Department of Corrections

One of the key statistics that Iowa Corrections maintains to measure the success of our efforts is the three-year return-to-prison rate for offenders leaving prison and reentering the community. As the chart below shows, the rate for the three-year period from FY 2009 through FY 2012 is the lowest since this measure has been calculated.

Prices of medicines: a case-study on the impact of the rate-of-return regulation in the United Kingdom

This work carries out an empirical evaluation of the impact of the main mechanism for regulating the prices of medicines in the UK on a variety ofpharmaceutical price indices. The empirical evidence shows that the overall impact of the rate of return cap appears to have been slight or even null, and in any case that the impact would differ across therapeutic areas. These empiricalfindings suggest that the price regulation has managed to encourage UK-based firms¿ diversification in many therapeutic areas

Lag-one autocorrelation in short series: Estimation and hypothesis testing

In the first part of the study, nine estimators of the first-order autoregressive parameter are reviewed and a new estimator is proposed. The relationships and discrepancies between the estimators are discussed in order to achieve a clear differentiation. In the second part of the study, the precision in the estimation of autocorrelation is studied. The performance of the ten lag-one autocorrelation estimators is compared in terms of Mean Square Error (combining bias and variance) using data series generated by Monte Carlo simulation. The results show that there is not a single optimal estimator for all conditions, suggesting that the estimator ought to be chosen according to sample size and to the information available of the possible direction of the serial dependence. Additionally, the probability of labelling an actually existing autocorrelation as statistically significant is explored using Monte Carlo sampling. The power estimates obtained are quite similar among the tests associated with the different estimators. These estimates evidence the small probability of detecting autocorrelation in series with less than 20 measurement times.

INTERMED predicts non-return to work in an occupational rehabilitation setting for individuals with orthopaedic trauma-part 2

Introduction.- The model presented in part I (19 predictors) had good predictive values for non-return to work 2 years after vocational rehabilitation for orthopaedic trauma. However, the number of predictors is high for the detection of patients at risk in a clinic. For example, the INTERMED for itself consists of 20 questions and needs 20 minutes to be filled in. For this reason, the aim of this study was to compare the predictive value of different models for the prediction of non-return to work.Patients and methods.- In this longitudinal prospective study, the cohort consisted of 2156 included inpatients with orthopaedic trauma attending a rehabilitation hospital after a work, traffic, sport or leisure related injury. Two years after discharge, 1502 patients returned a questionnaire regarding return to work. We compared the area under the receiver-operator-characteristics curve (ROC) between different models: INTERMED total score, the 4 partial INTERMED scores, the items of the most predictive partial score; with or without confounders.Results.- The ROC for the total score of the INTERMED plus the five confounders of the of the part one (qualified work, speaking French, lesion of upper extremity, education and age) was 0.72. The sole partial INTERMED score to predict return to work was the social sub score. The ROC for the five items of the latter sub score of the INTERMED was 0.69. The ROC for the five items of the social subscale of the INTERMED combined with five predictors was 0.73. This was significantly better than the use of only the five items from INTERMED alone (delta 0.034; 95% CI 0.017 to .050). The model presented in part I (INTERMED total score plus 18 predictors) was not significantly better than the five items INTERMED social score plus five confounders.Discussion.- The use of a model with ten variables (INTERMED social five items plus five confounders) has good predictive value to detect patients not returning to work after vocational rehabilitation after orthopaedic trauma. The parsimony of this model facilitates its use in a clinic for the detection of patients at risk.

Potential yield, return, and tree diversity of managed, uneven-aged Douglas-fir stands

Abstract

Thidiazuron effects on shoot growth, return bloom, fruit set and nutrition of apples

Apple (Malus domestica Borkh.) trees, cultivars Gala and Fuji, were sprayed at full bloom with thidiazuron (TDZ) at doses of 0, 5, 10, or 20 g ha-1 of a.i. in order to evaluate its effects on plant growth and development, return bloom, fruit set, nutrition, and fruit yield. Fruit set increased with TDZ dose in 'Gala' but not in 'Fuji'. TDZ did not affect fruit yield in any cultivar. In 'Gala', the return bloom was reduced in about 50% at TDZ doses of 10 or 20 g ha-1. TDZ increased shoot growth in both cultivars. In leaves, TDZ decreased the concentration of Ca and Mg in 'Gala' and of Mg in 'Fuji', but did not affect the chlorophyll content, leaf area, length, width, and dry mass per cm² regardless of cultivar. In fruits, the effect of TDZ varied according to the portion evaluated. Highest doses of TDZ decreased the concentration of Ca and K in 'Gala' and of K in 'Fuji' in the entire fruits (flesh + skin); in the skin, highest doses of TDZ reduced the levels of N, Ca, and Mg in both cultivars, in addition to the level of K in 'Fuji'.

Textual autocorrelation : formalism and illustrations

Abstract Textual autocorrelation is a broad and pervasive concept, referring to the similarity between nearby textual units: lexical repetitions along consecutive sentences, semantic association between neighbouring lexemes, persistence of discourse types (narrative, descriptive, dialogal...) and so on. Textual autocorrelation can also be negative, as illustrated by alternating phonological or morpho-syntactic categories, or the succession of word lengths. This contribution proposes a general Markov formalism for textual navigation, and inspired by spatial statistics. The formalism can express well-known constructs in textual data analysis, such as term-document matrices, references and hyperlinks navigation, (web) information retrieval, and in particular textual autocorrelation, as measured by Moran's I relatively to the exchange matrix associated to neighbourhoods of various possible types. Four case studies (word lengths alternation, lexical repulsion, parts of speech autocorrelation, and semantic autocorrelation) illustrate the theory. In particular, one observes a short-range repulsion between nouns together with a short-range attraction between verbs, both at the lexical and semantic levels. Résumé: Le concept d'autocorrélation textuelle, fort vaste, réfère à la similarité entre unités textuelles voisines: répétitions lexicales entre phrases successives, association sémantique entre lexèmes voisins, persistance du type de discours (narratif, descriptif, dialogal...) et ainsi de suite. L'autocorrélation textuelle peut être également négative, comme l'illustrent l'alternance entre les catégories phonologiques ou morpho-syntaxiques, ou la succession des longueurs de mots. Cette contribution propose un formalisme markovien général pour la navigation textuelle, inspiré par la statistique spatiale. Le formalisme est capable d'exprimer des constructions bien connues en analyse des données textuelles, telles que les matrices termes-documents, les références et la navigation par hyperliens, la recherche documentaire sur internet, et, en particulier, l'autocorélation textuelle, telle que mesurée par le I de Moran relatif à une matrice d'échange associée à des voisinages de différents types possibles. Quatre cas d'étude illustrent la théorie: alternance des longueurs de mots, répulsion lexicale, autocorrélation des catégories morpho-syntaxiques et autocorrélation sémantique. On observe en particulier une répulsion à courte portée entre les noms, ainsi qu'une attraction à courte portée entre les verbes, tant au niveau lexical que sémantique.

Density, climate and varying return points: an analysis of long-term population fluctuations in the threatened European tree frog.

Experimental research has identified many putative agents of amphibian decline, yet the population-level consequences of these agents remain unknown, owing to lack of information on compensatory density dependence in natural populations. Here, we investigate the relative importance of intrinsic (density-dependent) and extrinsic (climatic) factors impacting the dynamics of a tree frog (Hyla arborea) population over 22 years. A combination of log-linear density dependence and rainfall (with a 2-year time lag corresponding to development time) explain 75% of the variance in the rate of increase. Such fluctuations around a variable return point might be responsible for the seemingly erratic demography and disequilibrium dynamics of many amphibian populations.

Factors associated with 56-day non-return rate in dairy cattle

The objective of this work was to identify factors associated with the 56-day non-return rate (56-NRR) in dairy herds in the Galician region, Spain, and to estimate it for individual Holstein bulls. The experiment was carried out in herds originated from North-West Spain, from September 2008 to August 2009. Data of the 76,440 first inseminations performed during this period were gathered. Candidate factors were tested for their association with the 56-NRR by using a logistic model (binomial). Afterwards, 37 sires with a minimum of 150 first performed inseminations were individually evaluated. Logistic models were also estimated for each bull, and predicted individual 56-NRR rate values were calculated as a solution for the model parameters. Logistic regression found four major factors associated with 56-NRR in lactating cows: age at insemination, days from calving to insemination, milk production level at the time of insemination, and herd size. First-service conception rate, when a particular sire was used, was higher for heifers (0.71) than for lactating cows (0.52). Non-return rates were highly variable among bulls. Asignificant part of the herd-level variation of 56-NRR of Holstein cattle seems attributable to the service sire. High correlation level between observed and predicted 56-NRR was found.

The INTERMED questionnaire for predicting return to work after a multidisciplinary rehabilitation program for chronic low back pain.

OBJECTIVES: To evaluate the performance of the INTERMED questionnaire score, alone or combined with other criteria, in predicting return to work after a multidisciplinary rehabilitation program in patients with non-specific chronic low back pain. METHODS: The INTERMED questionnaire is a biopsychosocial assessment and clinical classification tool that separates heterogeneous populations into subgroups according to case complexity. We studied 88 patients with chronic low back pain who followed an intensive multidisciplinary rehabilitation program on an outpatient basis. Before the program, we recorded the INTERMED score, radiological abnormalities, subjective pain severity, and sick leave duration. Associations between these variables and return to full-time work within 3 months after the end of the program were evaluated using one-sided Fisher tests and univariate logistic regression followed by multivariate logistic regression. RESULTS: The univariate analysis showed a significant association between the INTERMED score and return to work (P<0.001; odds ratio, 0.90; 95% confidence interval, 0.86-0.96). In the multivariate analysis, prediction was best when the INTERMED score and sick leave duration were used in combination (P=0.03; odds ratio, 0.48; 95% confidence interval, 0.25-0.93). CONCLUSION: The INTERMED questionnaire is useful for evaluating patients with chronic low back pain. It could be used to improve the selection of patients for intensive multidisciplinary programs, thereby improving the quality of care, while reducing healthcare costs.

Predicting Non Return to Work after Orthopaedic Trauma: The Wallis Occupational Rehabilitation RisK (WORRK) Model.

BACKGROUND: Workers with persistent disabilities after orthopaedic trauma may need occupational rehabilitation. Despite various risk profiles for non-return-to-work (non-RTW), there is no available predictive model. Moreover, injured workers may have various origins (immigrant workers), which may either affect their return to work or their eligibility for research purposes. The aim of this study was to develop and validate a predictive model that estimates the likelihood of non-RTW after occupational rehabilitation using predictors which do not rely on the worker's background. METHODS: Prospective cohort study (3177 participants, native (51%) and immigrant workers (49%)) with two samples: a) Development sample with patients from 2004 to 2007 with Full and Reduced Models, b) External validation of the Reduced Model with patients from 2008 to March 2010. We collected patients' data and biopsychosocial complexity with an observer rated interview (INTERMED). Non-RTW was assessed two years after discharge from the rehabilitation. Discrimination was assessed by the area under the receiver operating curve (AUC) and calibration was evaluated with a calibration plot. The model was reduced with random forests. RESULTS: At 2 years, the non-RTW status was known for 2462 patients (77.5% of the total sample). The prevalence of non-RTW was 50%. The full model (36 items) and the reduced model (19 items) had acceptable discrimination performance (AUC 0.75, 95% CI 0.72 to 0.78 and 0.74, 95% CI 0.71 to 0.76, respectively) and good calibration. For the validation model, the discrimination performance was acceptable (AUC 0.73; 95% CI 0.70 to 0.77) and calibration was also adequate. CONCLUSIONS: Non-RTW may be predicted with a simple model constructed with variables independent of the patient's education and language fluency. This model is useful for all kinds of trauma in order to adjust for case mix and it is applicable to vulnerable populations like immigrant workers.