Success factors of product innovation:an updated meta-analysis

Assessing factors that predict new product success (NPS) holds critical importance for companies, as research shows that despite considerable new product investment, success rates are generally below 25%. Over the decades, meta-analytical attempts have been made to summarize empirical findings on NPS factors. However, market environment changes such as increased global competition, as well as methodological advancements in meta-analytical research, present a timely opportunity to augment their results. Hence, a key objective of this research is to provide an updated and extended meta-analytic investigation of the factors affecting NPS. Using Henard and Szymanski's meta-analysis as the most comprehensive recent summary of empirical findings, this study updates their findings by analyzing articles published from 1999 through 2011, the period following the original meta-analysis. Based on 233 empirical studies (from 204 manuscripts) on NPS, with a total 2618 effect sizes, this study also takes advantage of more recent methodological developments by re-calculating effects of the meta-analysis employing a random effects model. The study's scope broadens by including overlooked but important additional variables, notably “country culture,” and discusses substantive differences between the updated meta-analysis and its predecessor. Results reveal generally weaker effect sizes than those reported by Henard and Szymanski in 2001, and provide evolutionary evidence of decreased effects of common success factors over time. Moreover, culture emerges as an important moderating factor, weakening effect sizes for individualistic countries and strengthening effects for risk-averse countries, highlighting the importance of further investigating culture's role in product innovation studies, and of tracking changes of success factors of product innovations. Finally, a sharp increase since 1999 in studies investigating product and process characteristics identifies a significant shift in research interest in new product development success factors. The finding that the importance of success factors generally declines over time calls for new theoretical approaches to better capture the nature of new product development (NPD) success factors. One might speculate that the potential to create competitive advantages through an understanding of NPD success factors is reduced as knowledge of these factors becomes more widespread among managers. Results also imply that managers attempting to improve success rates of NPDs need to consider national culture as this factor exhibits a strong moderating effect: Working in varied cultural contexts will result in differing antecedents of successful new product ventures.

La thérapie cognitive-comportementale dans le traitement du TDAH chez l'adulte: état des connaissances

Essai doctoral présenté à la Faculté des Arts et des Sciences en vue de l'obtention du grade de doctorat en psychologie clinique (D.psy.)

La thérapie cognitive-comportementale dans le traitement du TDAH chez l'adulte: état des connaissances

Essai doctoral présenté à la Faculté des Arts et des Sciences en vue de l'obtention du grade de doctorat en psychologie clinique (D.psy.)

Conservative fluid management or deresuscitation for patients with sepsis or acute respiratory distress syndrome following the resuscitation phase of critical illness: a systematic review and meta-analysis

Background

It is unknown whether a conservative approach to fluid administration or deresuscitation (active removal of fluid using diuretics or renal replacement therapy) is beneficial following haemodynamic stabilisation of critically ill patients.

Purpose

To evaluate the efficacy and safety of conservative or deresuscitative fluid strategies in adults and children with acute respiratory distress syndrome (ARDS), sepsis or systemic inflammatory response syndrome (SIRS) in the post-resuscitation phase of critical illness.

Methods

We searched Medline, EMBASE and the Cochrane central register of controlled trials from 1980 to June 2016, and manually reviewed relevant conference proceedings from 2009 to the present. Two reviewers independently assessed search results for inclusion and undertook data extraction and quality appraisal. We included randomised trials comparing fluid regimens with differing fluid balances between groups, and observational studies investigating the relationship between fluid balance and clinical outcomes.

Results

Forty-nine studies met the inclusion criteria. Marked clinical heterogeneity was evident. In a meta-analysis of 11 randomised trials (2051 patients) using a random-effects model, we found no significant difference in mortality with conservative or deresuscitative strategies compared with a liberal strategy or usual care [pooled risk ratio (RR) 0.92, 95 % confidence interval (CI) 0.82–1.02, I2 = 0 %]. A conservative or deresuscitative strategy resulted in increased ventilator-free days (mean difference 1.82 days, 95 % CI 0.53–3.10, I2 = 9 %) and reduced length of ICU stay (mean difference −1.88 days, 95 % CI −0.12 to −3.64, I2 = 75 %) compared with a liberal strategy or standard care.

Conclusions

In adults and children with ARDS, sepsis or SIRS, a conservative or deresuscitative fluid strategy results in an increased number of ventilator-free days and a decreased length of ICU stay compared with a liberal strategy or standard care. The effect on mortality remains uncertain. Large randomised trials are needed to determine optimal fluid strategies in critical illness.

Cabazitaxel for Hormone-Relapsed Metastatic Prostate Cancer Previously Treated With a Docetaxel-Containing Regimen: An Evidence Review Group Perspective of a NICE Single Technology Appraisal

As part of its single technology appraisal (STA) process, the National Institute for Health and Care Excellence (NICE) invited the company that manufactures cabazitaxel (Jevtana(®), Sanofi, UK) to submit evidence for the clinical and cost effectiveness of cabazitaxel for treatment of patients with metastatic hormone-relapsed prostate cancer (mHRPC) previously treated with a docetaxel-containing regimen. The School of Health and Related Research Technology Appraisal Group at the University of Sheffield was commissioned to act as the independent Evidence Review Group (ERG). The ERG produced a critical review of the evidence for the clinical and cost effectiveness of the technology based upon the company's submission to NICE. Clinical evidence for cabazitaxel was derived from a multinational randomised open-label phase III trial (TROPIC) of cabazitaxel plus prednisone or prednisolone compared with mitoxantrone plus prednisone or prednisolone, which was assumed to represent best supportive care. The NICE final scope identified a further three comparators: abiraterone in combination with prednisone or prednisolone; enzalutamide; and radium-223 dichloride for the subgroup of people with bone metastasis only (no visceral metastasis). The company did not consider radium-223 dichloride to be a relevant comparator. Neither abiraterone nor enzalutamide has been directly compared in a trial with cabazitaxel. Instead, clinical evidence was synthesised within a network meta-analysis (NMA). Results from TROPIC showed that cabazitaxel was associated with a statistically significant improvement in both overall survival and progression-free survival compared with mitoxantrone. Results from a random-effects NMA, as conducted by the company and updated by the ERG, indicated that there was no statistically significant difference between the three active treatments for both overall survival and progression-free survival. Utility data were not collected as part of the TROPIC trial, and were instead taken from the company's UK early access programme. Evidence on resource use came from the TROPIC trial, supplemented by both expert clinical opinion and a UK clinical audit. List prices were used for mitoxantrone, abiraterone and enzalutamide as directed by NICE, although commercial in-confidence patient-access schemes (PASs) are in place for abiraterone and enzalutamide. The confidential PAS was used for cabazitaxel. Sequential use of the advanced hormonal therapies (abiraterone and enzalutamide) does not usually occur in clinical practice in the UK. Hence, cabazitaxel could be used within two pathways of care: either when an advanced hormonal therapy was used pre-docetaxel, or when one was used post-docetaxel. The company believed that the former pathway was more likely to represent standard National Health Service (NHS) practice, and so their main comparison was between cabazitaxel and mitoxantrone, with effectiveness data from the TROPIC trial. Results of the company's updated cost-effectiveness analysis estimated a probabilistic incremental cost-effectiveness ratio (ICER) of £45,982 per quality-adjusted life-year (QALY) gained, which the committee considered to be the most plausible value for this comparison. Cabazitaxel was estimated to be both cheaper and more effective than abiraterone. Cabazitaxel was estimated to be cheaper but less effective than enzalutamide, resulting in an ICER of £212,038 per QALY gained for enzalutamide compared with cabazitaxel. The ERG noted that radium-223 is a valid comparator (for the indicated sub-group), and that it may be used in either of the two care pathways. Hence, its exclusion leads to uncertainty in the cost-effectiveness results. In addition, the company assumed that there would be no drug wastage when cabazitaxel was used, with cost-effectiveness results being sensitive to this assumption: modelling drug wastage increased the ICER comparing cabazitaxel with mitoxantrone to over £55,000 per QALY gained. The ERG updated the company's NMA and used a random effects model to perform a fully incremental analysis between cabazitaxel, abiraterone, enzalutamide and best supportive care using PASs for abiraterone and enzalutamide. Results showed that both cabazitaxel and abiraterone were extendedly dominated by the combination of best supportive care and enzalutamide. Preliminary guidance from the committee, which included wastage of cabazitaxel, did not recommend its use. In response, the company provided both a further discount to the confidential PAS for cabazitaxel and confirmation from NHS England that it is appropriate to supply and purchase cabazitaxel in pre-prepared intravenous-infusion bags, which would remove the cost of drug wastage. As a result, the committee recommended use of cabazitaxel as a treatment option in people with an Eastern Cooperative Oncology Group performance status of 0 or 1 whose disease had progressed during or after treatment with at least 225 mg/m(2) of docetaxel, as long as it was provided at the discount agreed in the PAS and purchased in either pre-prepared intravenous-infusion bags or in vials at a reduced price to reflect the average per-patient drug wastage.

Adhésion au traitement antidiabétique oral chez les adultes atteints de diabète de type 2 : déterminants et interventions visant à l'améliorer

Introduction : Le diabète de type 2 est une maladie évolutive débilitante et souvent mortelle qui atteint de plus en plus de personnes dans le monde. Le traitement antidiabétique non-insulinique (TADNI) notamment le traitement antidiabétique oral (TADO) est le plus fréquemment utilisé chez les adultes atteints de cette maladie. Toutefois, plusieurs de ces personnes ne prennent pas leur TADO tel que prescrit posant ainsi la problématique d’une adhésion sous-optimale. Ceci entraîne des conséquences néfastes aussi bien pour les patients que pour la société dans laquelle ils vivent. Il serait donc pertinent d’identifier des pistes de solution à cette problématique. Objectifs : Trois objectifs de recherche ont été étudiés : 1) Explorer la capacité de la théorie du comportement planifié (TCP) à prédire l’adhésion future au TADNI chez les adultes atteints de diabète de type 2, 2) Évaluer l’efficacité globale des interventions visant à améliorer l’adhésion au TADO chez les adultes atteints de diabète de type 2 et étudier l’influence des techniques de changement de comportement sur cette efficacité globale, et 3) Évaluer l’efficacité globale de l’entretien motivationnel sur l’adhésion au traitement médicamenteux chez les adultes atteints de maladie chronique et étudier l’influence des caractéristiques de cette intervention sur son efficacité globale. Méthodes : Pour l’objectif 1 : Il s’agissait d’une enquête web, suivie d’une évaluation de l’adhésion au TADNI sur une période de 30 jours, chez des adultes atteints de diabète de type 2, membres de Diabète Québec. L’enquête consistait à la complétion d’un questionnaire auto-administré incluant les variables de la TCP (intention, contrôle comportemental perçu et attitude) ainsi que d’autres variables dites «externes». Les informations relatives au calcul de l’adhésion provenaient des dossiers de pharmacie des participants transmis via la plateforme ReMed. Une régression linéaire multivariée a été utilisée pour estimer la mesure d’association entre l’intention et l’adhésion future au TADNI ainsi que l’interaction entre l’adhésion passée et l’intention. Pour répondre aux objectifs 2 et 3, deux revues systématiques et méta-analyses ont été effectuées et rapportées selon les lignes directrices de PRISMA. Un modèle à effets aléatoires a été utilisé pour estimer l’efficacité globale (g d’Hedges) des interventions et son intervalle de confiance à 95 % (IC95%) dans chacune des revues. Nous avons également quantifié l’hétérogénéité (I2 d’Higgins) entre les études, et avons fait des analyses de sous-groupe et des analyses de sensibilité. Résultats : Objectif 1 : Il y avait une interaction statistiquement significative entre l’adhésion passée et l’intention (valeur-p= 0,03). L’intention n’était pas statistiquement associée à l’adhésion future au TADNI, mais son effet était plus fort chez les non-adhérents que chez les adhérents avant l’enquête web. En revanche, l’intention était principalement prédite par le contrôle comportemental perçu à la fois chez les adhérents [β= 0,90, IC95%= (0,80; 1,00)] et chez les non-adhérents passés [β= 0,76, IC95%= (0,56; 0,97)]. Objectif 2 : L’efficacité globale des interventions sur l’adhésion au TADO était de 0,21 [IC95%= (-0,05; 0,47); I2= 82 %]. L’efficacité globale des interventions dans lesquelles les intervenants aidaient les patients et/ou les cliniciens à être proactifs dans la gestion des effets indésirables était de 0,64 [IC95%= (0,31; 0,96); I2= 56 %]. Objectif 3 : L’efficacité globale des interventions (basées sur l’entretien motivationnel) sur l’adhésion au traitement médicamenteux était de 0,12 [IC95%= (0,05; 0,20); I2= 1 %. Les interventions basées uniquement sur l’entretien motivationnel [β= 0,18, IC95%= (0,00; 0,36)] et celles dans lesquelles les intervenants ont été coachés [β= 0,47, IC95%= (0,03; 0,90)] étaient les plus efficaces. Aussi, les interventions administrées en face-à-face étaient plus efficaces que celles administrées par téléphone [β= 0,27, IC95%=(0,04; 0,50)]. Conclusion : Il existe un écart entre l’intention et l’adhésion future au TADNI, qui est partiellement expliqué par le niveau d’adhésion passée. Toutefois, il n’y avait pas assez de puissance statistique pour démontrer une association statistiquement significative entre l’intention et l’adhésion future chez les non-adhérents passés. D’un autre côté, quelques solutions au problème de l’adhésion sous-optimale au TADO ont été identifiées. En effet, le fait d’aider les patients et/ou les cliniciens à être proactifs dans la gestion des effets indésirables contribue efficacement à l’amélioration de l’adhésion au TADO chez les adultes atteints de diabète de type 2. Aussi, les interventions basées sur l’entretien motivationnel améliorent efficacement l’adhésion au traitement médicamenteux chez les adultes atteints de maladie chronique. L’entretien motivationnel pourrait donc être utilisé comme un outil clinique pour soutenir les patients dans l’autogestion de leur TADO.

A Corrupção burocrática inibe o empreendedorismo? uma análise empírica dos estados brasileiros

This work aims to investigate the relationship between the entrepreneurship and the incidence of bureaucratic corruption in the states of Brazil and Federal District. The main hypothesis of this study is that the opening of a business in Brazilian states is negatively affected by the incidence of corruption. The theoretical reference is divided into Entrepreneurship and bureaucratic corruption, with an emphasis on materialistic perspective (objectivist) of entrepreneurship and the effects of bureaucratic corruption on entrepreneurial activity. By the regression method with panel data, we estimated the models with pooled data and fixed and random effects. To measure corruption, I used the General Index of Corruption for the Brazilian states (BOLL, 2010), and to represent entrepreneurship, firm entry per capita by state. Tests (Chow, Hausman and Breusch-Pagan) indicate that the random effects model is more appropriate, and the preliminary results indicate a positive impact of bureaucratic corruption on entrepreneurial activity, contradicting the hypothesis expected and found in previous articles to Brazil, and corroborating the proposition of Dreher and Gassebner (2011) that, in countries with high regulation, bureaucratic corruption can be grease in the wheels of entrepreneurship

A Corrupção burocrática inibe o empreendedorismo? uma análise empírica dos estados brasileiros

This work aims to investigate the relationship between the entrepreneurship and the incidence of bureaucratic corruption in the states of Brazil and Federal District. The main hypothesis of this study is that the opening of a business in Brazilian states is negatively affected by the incidence of corruption. The theoretical reference is divided into Entrepreneurship and bureaucratic corruption, with an emphasis on materialistic perspective (objectivist) of entrepreneurship and the effects of bureaucratic corruption on entrepreneurial activity. By the regression method with panel data, we estimated the models with pooled data and fixed and random effects. To measure corruption, I used the General Index of Corruption for the Brazilian states (BOLL, 2010), and to represent entrepreneurship, firm entry per capita by state. Tests (Chow, Hausman and Breusch-Pagan) indicate that the random effects model is more appropriate, and the preliminary results indicate a positive impact of bureaucratic corruption on entrepreneurial activity, contradicting the hypothesis expected and found in previous articles to Brazil, and corroborating the proposition of Dreher and Gassebner (2011) that, in countries with high regulation, bureaucratic corruption can be grease in the wheels of entrepreneurship

Modeling multivariate autoregressive conditional heteroskedasticity with the double smooth transition conditional correlation GARCH Model

In this paper, we propose a multivariate GARCH model with a time-varying conditional correlation structure. The new double smooth transition conditional correlation (DSTCC) GARCH model extends the smooth transition conditional correlation (STCC) GARCH model of Silvennoinen and Teräsvirta (2005) by including another variable according to which the correlations change smoothly between states of constant correlations. A Lagrange multiplier test is derived to test the constancy of correlations against the DSTCC-GARCH model, and another one to test for another transition in the STCC-GARCH framework. In addition, other specification tests, with the aim of aiding the model building procedure, are considered. Analytical expressions for the test statistics and the required derivatives are provided. Applying the model to the stock and bond futures data, we discover that the correlation pattern between them has dramatically changed around the turn of the century. The model is also applied to a selection of world stock indices, and we find evidence for an increasing degree of integration in the capital markets.

Bayesian estimation of the dynamics of pandemic (H1N1) 2009 influenza transmission in Queensland: A space–time SIR-based model

Background A pandemic strain of influenza A spread rapidly around the world in 2009, now referred to as pandemic (H1N1) 2009. This study aimed to examine the spatiotemporal variation in the transmission rate of pandemic (H1N1) 2009 associated with changes in local socio-environmental conditions from May 7–December 31, 2009, at a postal area level in Queensland, Australia. Method We used the data on laboratory-confirmed H1N1 cases to examine the spatiotemporal dynamics of transmission using a flexible Bayesian, space–time, Susceptible-Infected-Recovered (SIR) modelling approach. The model incorporated parameters describing spatiotemporal variation in H1N1 infection and local socio-environmental factors. Results The weekly transmission rate of pandemic (H1N1) 2009 was negatively associated with the weekly area-mean maximum temperature at a lag of 1 week (LMXT) (posterior mean: −0.341; 95% credible interval (CI): −0.370–−0.311) and the socio-economic index for area (SEIFA) (posterior mean: −0.003; 95% CI: −0.004–−0.001), and was positively associated with the product of LMXT and the weekly area-mean vapour pressure at a lag of 1 week (LVAP) (posterior mean: 0.008; 95% CI: 0.007–0.009). There was substantial spatiotemporal variation in transmission rate of pandemic (H1N1) 2009 across Queensland over the epidemic period. High random effects of estimated transmission rates were apparent in remote areas and some postal areas with higher proportion of indigenous populations and smaller overall populations. Conclusions Local SEIFA and local atmospheric conditions were associated with the transmission rate of pandemic (H1N1) 2009. The more populated regions displayed consistent and synchronized epidemics with low average transmission rates. The less populated regions had high average transmission rates with more variations during the H1N1 epidemic period.

A (semi-)parametric functional coefficient autoregressive conditional duration model

In this paper, we propose a class of ACD-type models that accommodates overdispersion, intermittent dynamics, multiple regimes, and sign and size asymmetries in financial durations. In particular, our functional coefficient autoregressive conditional duration (FC-ACD) model relies on a smooth-transition autoregressive specification. The motivation lies on the fact that the latter yields a universal approximation if one lets the number of regimes grows without bound. After establishing that the sufficient conditions for strict stationarity do not exclude explosive regimes, we address model identifiability as well as the existence, consistency, and asymptotic normality of the quasi-maximum likelihood (QML) estimator for the FC-ACD model with a fixed number of regimes. In addition, we also discuss how to consistently estimate using a sieve approach a semiparametric variant of the FC-ACD model that takes the number of regimes to infinity. An empirical illustration indicates that our functional coefficient model is flexible enough to model IBM price durations.

Using Bayesian methods for the estimation of uncertainty in complex statistical models

The research objectives of this thesis were to contribute to Bayesian statistical methodology by contributing to risk assessment statistical methodology, and to spatial and spatio-temporal methodology, by modelling error structures using complex hierarchical models. Specifically, I hoped to consider two applied areas, and use these applications as a springboard for developing new statistical methods as well as undertaking analyses which might give answers to particular applied questions. Thus, this thesis considers a series of models, firstly in the context of risk assessments for recycled water, and secondly in the context of water usage by crops. The research objective was to model error structures using hierarchical models in two problems, namely risk assessment analyses for wastewater, and secondly, in a four dimensional dataset, assessing differences between cropping systems over time and over three spatial dimensions. The aim was to use the simplicity and insight afforded by Bayesian networks to develop appropriate models for risk scenarios, and again to use Bayesian hierarchical models to explore the necessarily complex modelling of four dimensional agricultural data. The specific objectives of the research were to develop a method for the calculation of credible intervals for the point estimates of Bayesian networks; to develop a model structure to incorporate all the experimental uncertainty associated with various constants thereby allowing the calculation of more credible credible intervals for a risk assessment; to model a single day’s data from the agricultural dataset which satisfactorily captured the complexities of the data; to build a model for several days’ data, in order to consider how the full data might be modelled; and finally to build a model for the full four dimensional dataset and to consider the timevarying nature of the contrast of interest, having satisfactorily accounted for possible spatial and temporal autocorrelations. This work forms five papers, two of which have been published, with two submitted, and the final paper still in draft. The first two objectives were met by recasting the risk assessments as directed, acyclic graphs (DAGs). In the first case, we elicited uncertainty for the conditional probabilities needed by the Bayesian net, incorporated these into a corresponding DAG, and used Markov chain Monte Carlo (MCMC) to find credible intervals, for all the scenarios and outcomes of interest. In the second case, we incorporated the experimental data underlying the risk assessment constants into the DAG, and also treated some of that data as needing to be modelled as an ‘errors-invariables’ problem [Fuller, 1987]. This illustrated a simple method for the incorporation of experimental error into risk assessments. In considering one day of the three-dimensional agricultural data, it became clear that geostatistical models or conditional autoregressive (CAR) models over the three dimensions were not the best way to approach the data. Instead CAR models are used with neighbours only in the same depth layer. This gave flexibility to the model, allowing both the spatially structured and non-structured variances to differ at all depths. We call this model the CAR layered model. Given the experimental design, the fixed part of the model could have been modelled as a set of means by treatment and by depth, but doing so allows little insight into how the treatment effects vary with depth. Hence, a number of essentially non-parametric approaches were taken to see the effects of depth on treatment, with the model of choice incorporating an errors-in-variables approach for depth in addition to a non-parametric smooth. The statistical contribution here was the introduction of the CAR layered model, the applied contribution the analysis of moisture over depth and estimation of the contrast of interest together with its credible intervals. These models were fitted using WinBUGS [Lunn et al., 2000]. The work in the fifth paper deals with the fact that with large datasets, the use of WinBUGS becomes more problematic because of its highly correlated term by term updating. In this work, we introduce a Gibbs sampler with block updating for the CAR layered model. The Gibbs sampler was implemented by Chris Strickland using pyMCMC [Strickland, 2010]. This framework is then used to consider five days data, and we show that moisture in the soil for all the various treatments reaches levels particular to each treatment at a depth of 200 cm and thereafter stays constant, albeit with increasing variances with depth. In an analysis across three spatial dimensions and across time, there are many interactions of time and the spatial dimensions to be considered. Hence, we chose to use a daily model and to repeat the analysis at all time points, effectively creating an interaction model of time by the daily model. Such an approach allows great flexibility. However, this approach does not allow insight into the way in which the parameter of interest varies over time. Hence, a two-stage approach was also used, with estimates from the first-stage being analysed as a set of time series. We see this spatio-temporal interaction model as being a useful approach to data measured across three spatial dimensions and time, since it does not assume additivity of the random spatial or temporal effects.

Spatial prediction of N2O emissions in pasture : a Bayesian model averaging analysis

Nitrous oxide (N2O) is one of the greenhouse gases that can contribute to global warming. Spatial variability of N2O can lead to large uncertainties in prediction. However, previous studies have often ignored the spatial dependency to quantify the N2O - environmental factors relationships. Few researches have examined the impacts of various spatial correlation structures (e.g. independence, distance-based and neighbourhood based) on spatial prediction of N2O emissions. This study aimed to assess the impact of three spatial correlation structures on spatial predictions and calibrate the spatial prediction using Bayesian model averaging (BMA) based on replicated, irregular point-referenced data. The data were measured in 17 chambers randomly placed across a 271 m(2) field between October 2007 and September 2008 in the southeast of Australia. We used a Bayesian geostatistical model and a Bayesian spatial conditional autoregressive (CAR) model to investigate and accommodate spatial dependency, and to estimate the effects of environmental variables on N2O emissions across the study site. We compared these with a Bayesian regression model with independent errors. The three approaches resulted in different derived maps of spatial prediction of N2O emissions. We found that incorporating spatial dependency in the model not only substantially improved predictions of N2O emission from soil, but also better quantified uncertainties of soil parameters in the study. The hybrid model structure obtained by BMA improved the accuracy of spatial prediction of N2O emissions across this study region.

An investigation of the impact of various geographical scales for the specification of spatial dependence

Ecological studies are based on characteristics of groups of individuals, which are common in various disciplines including epidemiology. It is of great interest for epidemiologists to study the geographical variation of a disease by accounting for the positive spatial dependence between neighbouring areas. However, the choice of scale of the spatial correlation requires much attention. In view of a lack of studies in this area, this study aims to investigate the impact of differing definitions of geographical scales using a multilevel model. We propose a new approach -- the grid-based partitions and compare it with the popular census region approach. Unexplained geographical variation is accounted for via area-specific unstructured random effects and spatially structured random effects specified as an intrinsic conditional autoregressive process. Using grid-based modelling of random effects in contrast to the census region approach, we illustrate conditions where improvements are observed in the estimation of the linear predictor, random effects, parameters, and the identification of the distribution of residual risk and the aggregate risk in a study region. The study has found that grid-based modelling is a valuable approach for spatially sparse data while the SLA-based and grid-based approaches perform equally well for spatially dense data.

Parametric correlation functions to model the structure of permanent environmental (co)variances in milk yield random regression models

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)