Correcting Measurement Error Bias in Interaction Models with Small Samples

Several methods have been suggested to estimate non-linear models with interaction terms in the presence of measurement error. Structural equation models eliminate measurement error bias, but require large samples. Ordinary least squares regression on summated scales, regression on factor scores and partial least squares are appropriate for small samples but do not correct measurement error bias. Two stage least squares regression does correct measurement error bias but the results strongly depend on the instrumental variable choice. This article discusses the old disattenuated regression method as an alternative for correcting measurement error in small samples. The method is extended to the case of interaction terms and is illustrated on a model that examines the interaction effect of innovation and style of use of budgets on business performance. Alternative reliability estimates that can be used to disattenuate the estimates are discussed. A comparison is made with the alternative methods. Methods that do not correct for measurement error bias perform very similarly and considerably worse than disattenuated regression

The underestimation of compliance to direct help requests explained by adaptive sampling

Helping behavior is any intentional behavior that benefits another living being or group (Hogg & Vaughan, 2010). People tend to underestimate the probability that others will comply with their direct requests for help (Flynn & Lake, 2008). This implies that when they need help, they will assess the probability of getting it (De Paulo, 1982, cited in Flynn & Lake, 2008) and then they will tend to estimate one that is actually lower than the real chance, so they may not even consider worth asking for it. Existing explanations for this phenomenon attribute it to a mistaken cost computation by the help seeker, who will emphasize the instrumental cost of “saying yes”, ignoring that the potential helper also needs to take into account the social cost of saying “no”. And the truth is that, especially in face-to-face interactions, the discomfort caused by refusing to help can be very high. In short, help seekers tend to fail to realize that it might be more costly to refuse to comply with a help request rather than accepting. A similar effect has been observed when estimating trustworthiness of people. Fetchenhauer and Dunning (2010) showed that people also tend to underestimate it. This bias is reduced when, instead of asymmetric feedback (getting feedback only when deciding to trust the other person), symmetric feedback (always given) was provided. This cause could as well be applicable to help seeking as people only receive feedback when they actually make their request but not otherwise. Fazio, Shook, and Eiser (2004) studied something that could be reinforcing these outcomes: Learning asymmetries. By means of a computer game called BeanFest, they showed that people learn better about negatively valenced objects (beans in this case) than about positively valenced ones. This learning asymmetry esteemed from “information gain being contingent on approach behavior” (p. 293), which could be identified with what Fetchenhauer and Dunning mention as ‘asymmetric feedback’, and hence also with help requests. Fazio et al. also found a generalization asymmetry in favor of negative attitudes versus positive ones. They attributed it to a negativity bias that “weights resemblance to a known negative more heavily than resemblance to a positive” (p. 300). Applied to help seeking scenarios, this would mean that when facing an unknown situation, people would tend to generalize and infer that is more likely that they get a negative rather than a positive outcome from it, so, along with what it was said before, people will be more inclined to think that they will get a “no” when requesting help. Denrell and Le Mens (2011) present a different perspective when trying to explain judgment biases in general. They deviate from the classical inappropriate information processing (depicted among other by Fiske & Taylor, 2007, and Tversky & Kahneman, 1974) and explain this in terms of ‘adaptive sampling’. Adaptive sampling is a sampling mechanism in which the selection of sample items is conditioned by the values of the variable of interest previously observed (Thompson, 2011). Sampling adaptively allows individuals to safeguard themselves from experiences they went through once and turned out to lay negative outcomes. However, it also prevents them from giving a second chance to those experiences to get an updated outcome that could maybe turn into a positive one, a more positive one, or just one that regresses to the mean, whatever direction that implies. That, as Denrell and Le Mens (2011) explained, makes sense: If you go to a restaurant, and you did not like the food, you do not choose that restaurant again. This is what we think could be happening when asking for help: When we get a “no”, we stop asking. And here, we want to provide a complementary explanation for the underestimation of the probability that others comply with our direct help requests based on adaptive sampling. First, we will develop and explain a model that represents the theory. Later on, we will test it empirically by means of experiments, and will elaborate on the analysis of its results.

Measuring intergenerational earnings mobility in Spain: a selection-bias-free approach

This paper analyses intergenerational earnings mobility in Spain correcting for different selection biases. We address the co-residence selection problem by combining information from two samples and using the two-sample two-stage least square estimator. We find a small decrease in elasticity when we move to younger cohorts. Furthermore, we find a higher correlation in the case of daughters than in the case of sons; however, when we consider the employment selection in the case of daughters, by adopting a Heckman-type correction method, the diference between sons and daughters disappears. By decomposing the sources of earnings elasticity across generations, we find that the correlation between child's and father's occupation is the most important component. Finally, quantile regressions estimates show that the influence of the father's earnings is greater when we move to the lower tail of the offspring's earnings distribution, especially in the case of daughters' earnings.

Selection bias and unobservable heterogeneity applied at the wage equation of European married women

This paper utilizes a panel data sample selection model to correct the selection in the analysis of longitudinal labor market data for married women in European countries. We estimate the female wage equation in a framework of unbalanced panel data models with sample selection. The wage equations of females have several potential sources of.

How to avoid gender bias in classroom interaction? A cooperative learning experience

This project aims to analyse the kind of questions the teacher asks students in order to encourage them to participate in her classes. Consequently, the researcher has read relevant literature and has analysed a short excerpt of a video recorded during her first practicum. She has also analysed a number of activities carried out during her second practicum in order to find out if she had improved her questioning skills in the classroom

Interpolation and sampling in small Bergman spaces

"Vegeu el resum a l'inici del document del fitxer adjunt."

Medical image registration based on random line sampling

One of the key aspects in 3D-image registration is the computation of the joint intensity histogram. We propose a new approach to compute this histogram using uniformly distributed random lines to sample stochastically the overlapping volume between two 3D-images. The intensity values are captured from the lines at evenly spaced positions, taking an initial random offset different for each line. This method provides us with an accurate, robust and fast mutual information-based registration. The interpolation effects are drastically reduced, due to the stochastic nature of the line generation, and the alignment process is also accelerated. The results obtained show a better performance of the introduced method than the classic computation of the joint histogram

Irregular to regular sampling, denoising and deconvolution

We propose a restoration algorithm for band limited images that considers irregular(perturbed) sampling, denoising, and deconvolution. We explore the application of a family ofregularizers that allow to control the spectral behavior of the solution combined with the irregular toregular sampling algorithms proposed by H.G. Feichtinger, K. Gr¨ochenig, M. Rauth and T. Strohmer.Moreover, the constraints given by the image acquisition model are incorporated as a set of localconstraints. And the analysis of such constraints leads to an early stopping rule meant to improvethe speed of the algorithm. Finally we present experiments focused on the restoration of satellite images, where the micro-vibrations are responsible of the type of distortions we are considering here. We will compare results of the proposed method with previous methods and show an extension tozoom.

The skill bias of world trade

Under plausible assumptions about preferences and technology, the model in this papersuggests that the entire volume of world trade matters for wage inequality. Therefore,trade integration, even among identical countries, is likely to increase the skill premium.Further, we argue that empirical evidence of a falling relative price of skill-intensive goods can be reconciled with the fast growth of world trade and that the intersectoral mobility of capital exacerbates the effect of trade on inequality. We provide new empirical evidence in support of our results and a quantitative assessment of the skill bias of world trade.

On commercial media bias

Within the spokes model of Chen and Riordan (2007) that allowsfor non-localized competition among arbitrary numbers of media outlets, we quantify the effect of concentration of ownership on qualityand bias of media content. A main result shows that too few commercial outlets, or better, too few separate owners of commercial outlets can lead to substantial bias in equilibrium. Increasing the number of outlets (commercial and non-commercial) tends to bring down this bias; but the strongest effect occurs when the number of owners is increased. Allowing for free entry provides lower bounds on fixed costs above which substantial commercial bias occurs in equilibrium.

Ambiguity seeking as a result of the status quo bias

Several factors affect attitudes toward ambiguity. What happens, however, when peopleare asked to exchange an ambiguous alternative in their possession for an unambiguousone? We present three experiments in which individuals preferred to retain the former.This status quo bias emerged both within- and between-subjects, with and withoutincentives, with different outcome distributions, and with endowments determined byboth the experimenter and the participants themselves. Findings emphasize the need toaccount for the frames of reference under which evaluations of probabilistic informationtake place as well as modifications that should be incorporated into descriptive modelsof decision making.

What risks do people perceive in everyday life? A perspective gained from the experience sampling method (ESM)

The experiential sampling method (ESM) was used to collect data from 74 parttimestudents who described and assessed the risks involved in their current activitieswhen interrupted at random moments by text messages. The major categories ofperceived risk were short-term in nature and involved loss of time or materials relatedto work and physical damage (e.g., from transportation). Using techniques of multilevelanalysis, we demonstrate effects of gender, emotional state, and types of risk onassessments of risk. Specifically, females do not differ from males in assessing thepotential severity of risks but they see these as more likely to occur. Also, participantsassessed risks to be lower when in more positive self-reported emotional states. Wefurther demonstrate the potential of ESM by showing that risk assessments associatedwith current actions exceed those made retrospectively. We conclude by notingadvantages and disadvantages of ESM for collecting data about risk perceptions.

Measuring risk aversion with lists: A new bias

Various experimental procedures aimed at measuring individual risk aversion involve alist of pairs of alternative prospects. We first study the widely used method by Holt andLaury (2002), for which we find that the removal of some items from the lists yields asystematic decrease in risk aversion. This bias is quite distinct from other confoundsthat have been previously observed in the use of the Holt and Laury method. It may berelated to empirical phenomena and theoretical developments where better prospectsincrease risk aversion. Nevertheless, we have also found that the more recent elicitationmethod due to Abdellaoui et al. (2011), also based on lists, does not display anystatistically significant bias when the corresponding items of the list are removed. Ourresults suggest that methods other than the popular Holt and Laury one may bepreferable for the measurement of risk aversion.

Fine-Tuning Translation Kinetics Selection as the Driving Force of Codon Usage Bias in the Hepatitis A Virus Capsid

Hepatitis A virus (HAV), the prototype of genus Hepatovirus, has several unique biological characteristics that distinguish it from other members of the Picornaviridae family. Among these, the need for an intact eIF4G factor for the initiation of translation results in an inability to shut down host protein synthesis by a mechanism similar to that of other picornaviruses. Consequently, HAV must inefficiently compete for the cellular translational machinery and this may explain its poor growth in cell culture. In this context of virus/cell competition, HAV has strategically adopted a naturally highly deoptimized codon usage with respect to that of its cellular host. With the aim to optimize its codon usage the virus was adapted to propagate in cells with impaired protein synthesis, in order to make tRNA pools more available for the virus. A significant loss of fitness was the immediate response to the adaptation process that was, however, later on recovered and more associated to a re-deoptimization rather than to an optimization of the codon usage specifically in the capsid coding region. These results exclude translation selection and instead suggest fine-tuning translation kinetics selection as the underlying mechanism of the codon usage bias in this specific genome region. Additionally, the results provide clear evidence of the Red Queen dynamics of evolution since the virus has very much evolved to re-adapt its codon usage to the environmental cellular changing conditions in order to recover the original fitness.