Modeling Unobserved Consideration Sets for Household Panel Data

We propose a new method to model consumers' consideration and choice processes. We develop a parsimonious probit type model for consideration and a multinomial probit model for choice, given consideration. Unlike earlier models of consideration ours is not prone to the curse of dimensionality, while we allow for very general structures of unobserved dependence in consideration among brands. In addition, our model allows for state dependence and marketing mix effects on consideration.Unique to this study is that we attempt to establish the validity of existing practice to infer consideration sets from observed choices in panel data. To this end, we use data collected in an on-line choice experiment involving interactive supermarket shelves and post-choice questionnaires to measure the choice protocol and stated consideration levels. We show with these experimental data that underlying consideration sets can be successfully retrieved from choice data alone and that there is substantial convergent validity of the stated and inferred consideration sets. We further find that consideration is a function of point-of-purchase marketing actions such as display and shelf space, and of consumer memory for recent choices.Next, we estimate the model on IRI panel data. We have three main results. First, compared with the single-stage probit model, promotion effects are larger and are inferred with smaller variances when they are included in the consideration stage of the two-stage model. Promotion effects are significant only in the two-stage model that includes consideration, whereas they are not in a single-stage choice model. Second, the price response curves of the two models are markedly diferent. The two-stage model offers a nice intuition for why promotional price response is different from regular price response. In addition and consistent with intuition, the two-stage model also implies that merchandizing has more effect on choice among those who did not buy the brand before than among those who already did. It is explained why a single-stage model does not harbor this feature. In fact, the single-stage model implies the opposite for smaller or more expensive brands. Third, we find that the consideration of brands does not covary greatly across brands once we take account of observed effects. Managerial implications and future research are also discussed.Consideration;choice;probit models

Consideration sets, intentions and the inclusion of "Don't know" in a two-stage model for voter choice

We present a statistical model for voter choice that incorporates a consideration set stage and final vote intention stage. The first stageinvolves a multivariate probit model for the vector of probabilities that a candidate or a party gets considered. The second stage of the model is a multinomial probit model for the actual choice. In both stages we use asexplanatory variables data on voter choice at the previous election, as well as socio-demographic respondent characteristics. Importantly, our modelexplicitly accounts for the three types of "missing data" encountered in polling. First, we include a no-vote option in the final vote intention stage. Second, the "do not know" response is assumed to arise from too little difference in the utility between the two most preferred options in the consideration set. Third, the "do not want to say" response is modelled as a missing observation on the most preferred alternative in the consideration set. Thus, we consider the missing data generating mechanism to be non-ignorable and build a model based on utility maximization to describe the voting intentions of these respondents. We illustrate the merits of the model as we have information on a sample of about 5000 individuals from the Netherlands for who we know how they voted last time (if at all), which parties they would consider for the upcoming election,and what their voting intention is. A unique feature of the data set is that information is available on actual individual voting behavior, measured at the day of election. We find that the inclusion of the consideration set stage in the model enables the user to make more precise inferences on the competitive structure in the political domain and to get better out-of-sample forecasts.Bayesian method;Choice model;Election data;Polling;Probit model

Hoe betalen we eigenlijk?

Het is voor sommige mensen nog even wennen, die euro. In het Duitse Erbach bleek een pompbediende nog niet helemaal op de hoogte van de nieuwe biljetten. Een klant rekende daar af met een biljet van 300 euro. Netjes kreeg hij vervolgens 250 euro terug

Retrieving unobserved consideration sets from household panel data

We propose a new model to describe consideration, consisting of a multivariate probit model component for consideration and a multinomial probit model component for choice, given consideration. The approach allows one to analyze stated consideration set data, revealed consideration set (choice) data or both, while at the same time it allows for unobserved dependence in consideration among brands. In addition, the model accommodates different effects of the marketing mix on consideration and choice, an error process that is correlated over time, and unobserved consumer heterogeneity in both processes. We attempt to establish the validity of existing practice to infer consideration sets from observed choices in panel data. To this end, we collect data in an on-line choice experiment involving interactive supermarket shelves and post-choice questionnaires to measure the choice protocol and stated consideration levels. We show with these experimental data that underlying consideration sets can be reliably retrieved from choice data alone. Next, we estimate the model on IRI panel data. We have two main results. First, compared with the single-stage multinomial probit model, promotion effects are larger when they are included in the consideration stage of the two-stage model. Second, we find that consideration of brands does not covary greatly across brands once we account for observed effects

Consideration sets, intentions and the inclusion of "Don't know" in a two-stage model for voter choice

We present a statistical model for voter choice that incorporates a consideration set stage and final vote intention stage. The first stage involves a multivariate probit model for the vector of probabilities that a candidate or a party gets considered. The second stage of the model is a multinomial probit model for the actual choice. In both stages we use as explanatory variables data on voter choice at the previous election, as well as socio-demographic respondent characteristics. Importantly, our model explicitly accounts for the three types of "missing data" encountered in polling. First, we include a no-vote option in the final vote intention stage. Second, the "do not know" response is assumed to arise from too little difference in the utility between the two most preferred options in the consideration set. Third, the "do not want to say" response is modelled as a missing observation on the most preferred alternative in the consideration set. Thus, we consider the missing data generating mechanism to be non-ignorable and build a model based on utility maximization to describe the voting intentions of these respondents. We illustrate the merits of the model as we have information on a sample of about 5000 individuals from the Netherlands for who we know how they voted last time (if at all), which parties they would consider for the upcoming election, and what their voting intention is. A unique feature of the data set is that in

Тактика лечения эректильной дисфункции у мужчин без партнерши

Обосновывается актуальность проблемы оказания помощи мужчинам с эректильной дисфункцией, не имеющим сексуальной партнерши. Описаны предложенные автором подходы к коррекции нарушения сексуального здоровья мужчин и лечебные тактики.The importance of the issue of rendering the aid to the men with erectile dysfunction who do not have a female partner is substantiated. The author describes the original approaches to correction of the sexual health in the men and therapeutic tactics

Childhood trauma, BDNF Val66Met and subclinical psychotic experiences. Attempt at replication in two independent samples

Childhood trauma exposure is a robust environmental risk factor for psychosis. However, not all exposed individuals develop psychotic symptoms later in life. The Brain-derived neurotrophic factor (BDNF) Val66Met polymorphism (rs6265) has been suggested to moderate the psychosis-inducing effects of childhood trauma in clinical and nonclinical samples. Our study aimed to explore the interaction effect between childhood trauma and the BDNF Val66Met polymorphism on subclinical psychotic experiences (PEs). This was explored in two nonclinical independent samples: an undergraduate and technical-training school student sample (n = 808, sample 1) and a female twin sample (n = 621, sample 2). Results showed that childhood trauma was strongly associated with positive and negative PEs in nonclinical individuals. A BDNF Val66Met x childhood trauma effect on positive PEs was observed in both samples. These results were discordant in terms of risk allele: while in sample 1 Val allele carriers, especially males, were more vulnerable to the effects of childhood trauma regarding PEs, in sample 2 Met carriers presented higher PEs scores when exposed to childhood trauma, compared with Val carriers. Moreover, in sample 2, a significant interaction was also found in relation to negative PEs. Our study partially replicates previous findings and suggests that some individuals are more prone to develop PEs following childhood trauma because of a complex combination of multiple factors. Further studies including genetic, environmental and epigenetic factors may provide insights in this field

Sculpting the Extra Dimensions: Inflation from Codimension-2 Brane Back-reaction

We construct an inflationary model in 6D supergravity that is based on explicit time-dependent solutions to the full higher-dimensional field equations, back-reacting to the presence of a 4D inflaton rolling on a space-filling codimension-2 source brane. Fluxes in the bulk stabilize all moduli except the `breathing' modulus (that is generically present in higher-dimensional supergravities). Back-reaction to the inflaton roll causes the 4D Einstein-frame on-brane geometry to expand, a(t) ~ t^p, as well as exciting the breathing mode and causing the two off-brane dimensions to expand, r(t) ~ t^q. The model evades the general no-go theorems precluding 4D de Sitter solutions, since adjustments to the brane-localized inflaton potential allow the power p to be dialed to be arbitrarily large, with the 4D geometry becoming de Sitter in the limit p -> infinity (in which case q = 0). Slow-roll solutions give accelerated expansion with p large but finite, and q = 1/2. Because the extra dimensions expand during inflation, the present-day 6D gravity scale can be much smaller than it was when primordial fluctuations were generated - potentially allowing TeV gravity now to be consistent with the much higher gravity scale required at horizon-exit for observable primordial gravity waves. Because p >> q, the 4 on-brane dimensions expand more quickly than the 2 off-brane ones, providing a framework for understanding why the observed four dimensions are presently so much larger than the internal two. If uplifted to a 10D framework with 4 dimensions stabilized, the 6D evolution described here could describe how two of the six extra dimensions evolve to become much larger than the others, as a consequence of the enormous expansion of the 4 large dimensions we can see.Comment: 27 pages + appendices, 2 figure

Salvage treatment for recurrences after first resection of colorectal liver metastases: the impact of histopathological growth patterns

The majority of patients recur after resection of colorectal liver metastases (CRLM). Patients with CRLM displaying a desmoplastic histopathological growth pattern (dHGP) have a better prognosis and lower probability of recurrence than patients with non-dHGP CRLM. The current study evaluates the impact of HGP type on the pattern and treatment of recurrences after first resection of CRLM. A retrospective cohort study was performed, including patients with known HGP type after complete resection of CRLM. All patients were treated between 2000 and 2015. The HGP was determined on the CRLM resected at first partial hepatectomy. The prognostic value of HGPs, in terms of survival outcome, in the current patient cohort were previously published. In total 690 patients were included, of which 492 (71%) developed recurrent disease. CRLM displaying dHGP were observed in 103 patients (21%). Amongst patients with dHGP CRLM diagnosed with recurrent disease, more liver-limited recurrences were seen (43% vs. 31%, p=0.030), whereas patients with non-dHGP more often recurred at multiple locations (34% vs. 19%, p=0.005). Patients with dHGP CRLM were more likely to undergo curatively intended local treatment for recurrent disease (adjusted odds ratio: 2.37; 95% confidence interval (CI) [1.46–3.84]; p<0.001) compared to patients with non-dHGP. The present study demonstrates that liver-limited disease recurrence after complete resection o