Systematic reviews and meta-analyses of diagnostic test accuracy

AbstractSystematic reviews of diagnostic test accuracy summarize the accuracy, e.g. the sensitivity and specificity, of diagnostic tests in a systematic and transparent way. The aim of such a review is to investigate whether a test is sufficiently specific or sensitive to fit its role in practice, to compare the accuracy of two or more diagnostic tests, or to investigate where existing variation in results comes from. The search strategy should be broad and preferably fully reported, to enable readers to assess the completeness of it. Included studies usually have a cross-sectional design in which the tests of interest, ideally both the index test and its comparator, are evaluated against the reference standard. They should be a reflection of the situation that the review question refers to. The quality of included studies is assessed with the Quality Assessment of Diagnostic Accuracy Studies-2 checklist, containing items such as a consecutive and all-inclusive patient selection process, blinding of index test and reference standard assessment, a valid reference standard, and complete verification of all included participants. Studies recruiting cases separately from (healthy) controls are regarded as bearing a high risk of bias. For meta-analysis, the bivariate model or the hierarchical summary receiver operating characteristic model is used. These models take into account potential threshold effects and the correlation between sensitivity and specificity. They also allow addition of covariates for investigatation of potential sources of heterogeneity. Finally, the results from the meta-analyses should be explained and interpreted for the reader, to be well understood

Co-branding: the state of the art

In this study I critically review models that specify competitive reaction effects. I discuss different model structures and summarize my findings on competitive reaction effects and factors that explain competitive reactions. I discuss the many models of competitive market response that have been developed and classify them into twelve sets of models that are related to each other in a logical manner through the evolutionary model-building concept.In this study I critically review models that specify competitive reaction effects. I discuss different model structures and summarize my findings on competitive reaction effects and factors that explain competitive reactions. I discuss the many models of competitive market response that have been developed and classify them into twelve sets of models that are related to each other in a logical manner through the evolutionary model-building concept.Articles published in or submitted to a Journal without I

Modeling Competitive Reaction Effects

In this study I critically review models that specify competitive reaction effects. I discuss different model structures and summarize my findings on competitive reaction effects and factors that explain competitive reactions. I discuss the many models of competitive market response that have been developed and classify them into twelve sets of models that are related to each other in a logical manner through the evolutionary model-building concept.In this study I critically review models that specify competitive reaction effects. I discuss different model structures and summarize my findings on competitive reaction effects and factors that explain competitive reactions. I discuss the many models of competitive market response that have been developed and classify them into twelve sets of models that are related to each other in a logical manner through the evolutionary model-building concept.Articles published in or submitted to a Journal without I

Semiparametric analysis to estimate the deal effect curve

The marketing literature suggests several phenomena that may contribute to the shape of the relationship between sales and price discounts. These phenomena can produce severe nonlinearities and interactions in the curves, and we argue that those are best captured with a flexible approach. Since a fully nonparametric regression model suffers from the curse of dimensionality, we propose a semiparametric regression model. Store-level sales over time is modeled as a nonparametric function of own-and cross-item price discounts, and a parametric function of other predictors (all indicator variables). We compare the predictive validity of the semiparametric model with that of two parametric benchmark models and obtain better performance on average. The results for three product categories indicate a.o. threshold- and saturation effects for both own- and cross-item temporary price cuts. We also show how the own-item curve depends on other items’ price discounts (flexible interaction effects). In a separate analysis, we show how the shape of the deal effect curve depends on own-item promotion signals. Our results indicate that prevailing methods for the estimation of deal effects on sales are inadequate.

Marketing in the Era of COVID-19

We discuss the effects of COVID-19 on consumer behaviour and elaborate on theconsequences of this disruption for marketing strategies and marketing policies. Thecrisis shows similarities with changes in consumer behaviour and the way marketingis carried out during economic downturns. However, it also displays characteristicswhich differ from downcycles, such as shifts in consumption between categories andthe accelerated shift from offline to online behaviour. This is forced by the re-evaluation of life priorities by final consumers