Parametric regression models are often not flexible enough to capture the true relationships as t... more Parametric regression models are often not flexible enough to capture the true relationships as they tend to rely on arbitrary identification assumptions. Using the UK Labor Force Survey, we estimate the causal effect of national minimum wage (NMW) increases on the probability of job entry and job exit by means of a non parametric Bayesian modelling approach known as Bayesian Additive Regression Trees (BART). This procedure is simple, flexible and it does not require ad-hoc assumptions about model fitting, number of covariates and how they interact. We find that the NMW exerts a positive and significant impact on both the probability of job entry and job exit. Although the magnitude of the effect on job entry is higher, the overall effect of NMW is ambiguous as there are lot of more employed workers. This can explain the insignificant effect found in the previous studies based on aggregate macroeconomic data. Furthermore, the causal effect of NMW is higher for young workers and in p...
This paper presents a step-by-step tutorial to estimate causal effects in PISA 2012 by means of a... more This paper presents a step-by-step tutorial to estimate causal effects in PISA 2012 by means of a nonparametric Bayesian modeling approach known as Bayesian Additive Regression Trees (BART), with an illustration of the causal impact of ICT on Spanish students' performance. The R code is explained in a way that can be easily applied to other similar studies. The application shows that, compared to more traditional methodologies, the BART approach is particularly useful when a high-dimensional set of confounding variables is considered as its results are not based on a sampling hypothesis. BART allows for the estimation of different interactive effects between the treatment variable and other covariates. BART models do not require the analyst to make explicit subjective decisions in which covariates must be included in the final models. This makes it an easy procedure to guide policy makers' decisions in different contexts
The gamma-aminobutyric acid type A (GABA(A)) receptor is an important pharmacological target of e... more The gamma-aminobutyric acid type A (GABA(A)) receptor is an important pharmacological target of ethanol. The effect of ethanol withdrawal on the expression of the alpha(2) subunit of this receptor was examined with rat cerebellar granule cells in primary culture. Long-term exposure of these cells to ethanol (100 mM, 5 days) did not affect the abundance of the mRNA for the alpha(2) subunit, as revealed by an RNase protection assay. In contrast, subsequent ethanol withdrawal for 3 h induced a marked increase in the amount of this mRNA (2.6-fold) as well as in that of the encoded polypeptide (2.2-fold), the latter revealed by immunoblot analysis. Exposure of the cells to gamma-hydroxybutyric acid (100 mM) during ethanol withdrawal prevented the increase in the amounts of both the alpha(2) mRNA and polypeptide, whereas similar treatment with diazepam (10 microM) blocked the increase in the abundance of the alpha(2) polypeptide but not that in the amount of the alpha(2) mRNA. The effect ...
This work proposes a semi-parametric approach to estimate the evolution of COVID-19 (SARS-CoV-2) ... more This work proposes a semi-parametric approach to estimate the evolution of COVID-19 (SARS-CoV-2) in Spain. Considering the sequences of 14-day cumulative incidence of all Spanish regions, it combines modern Deep Learning (DL) techniques for analyzing sequences with the usual Bayesian Poisson-Gamma model for counts. The DL model provides a suitable description of the observed time series of counts, but it cannot give a reliable uncertainty quantification. The role of expert elicitation of the expected number of counts and its reliability is DL predictions’ role in the proposed modelling approach. Finally, the posterior predictive distribution of counts is obtained in a standard Bayesian analysis using the well known Poisson-Gamma model. The model allows to predict the future evolution of the sequences on all regions or estimates the consequences of eventual scenarios.
The variable selection problem in general, and specifically for the ordinary linear regression mo... more The variable selection problem in general, and specifically for the ordinary linear regression model, is considered in the setup in which the number of covariates is large enough to prevent the exploration of all possible models. In this context, Gibbs-sampling is needed to perform stochastic model exploration to estimate, for instance, the model inclusion probability. We show that under a Bayesian non-parametric prior model for analyzing Gibbs-sampling output, the usual empirical estimator is just the asymptotic version of the expected posterior inclusion probability given the simulation output from Gibbs-sampling. Other posterior conditional estimators of inclusion probabilities can also be considered as related to the latent probabilities distributions on the model space which can be sampled given the observed Gibbs-sampling output. This paper will also compare, in this large model space setup the conventional prior approach against the non-local prior approach used to define the...
Caves are an extreme environment for humans because of the high humidity, mud, darkness, and slip... more Caves are an extreme environment for humans because of the high humidity, mud, darkness, and slippery conditions. Explorations can last many hours or even days, and require extensive climbing and ropework. Very little is known about the physical capacity of cavers and their energy expenditure (EE) during caving. The physical capacity of 17 (7 females) expert cavers (age 43.9 ± 7.3 years) was assessed during an incremental cycle-ergometer test (IET) with gas exchange analysis. Moreover, a wearable metabolic band (Armband Fit Core) was used to estimate their EE during caving. In terms of physical capacity, the IET showed that cavers had a maximum oxygen uptake (VO) of 2,248.7 ± 657.8 ml·min(i.e., 32.4 ± 6.4 ml·kg·min), while anaerobic threshold (AT) occurred on average at 74.5% of VO. Results from caving sessions provided an average time spent in cave of 9.4 ± 1.2 h while the average EE was 268.8 ± 54.8 kcal·h, which corresponded to about 40% of VOmeasured during IET. A mean distance ...
Economics: The Open-Access, Open-Assessment E-Journal
Parametric regression models are often not flexible enough to capture the true relationships as t... more Parametric regression models are often not flexible enough to capture the true relationships as they tend to rely on arbitrary identification assumptions. Using the UK Labor Force Survey, the authors estimate the causal effect of national minimum wage (NMW) increases on the probability of job entry and job exit by means of a non-parametric Bayesian modelling approach known as Bayesian Additive Regression Trees (BART). The application of this methodology has the important advantage that it does not require ad-hoc assumptions about model fitting, number of covariates and how they interact. They find that the NMW exerts a positive and significant impact on both the probability of job entry and job exit. Although the magnitude of the effect on job entry is higher, the overall effect of NMW is ambiguous as there are many more employed workers. The causal effect of NMW is higher for young workers and in periods of high unemployment and they have a stronger impact on job entry decisions. N...
Organoleptic properties, and more specifically chemosensory cues, have been shown to guide therap... more Organoleptic properties, and more specifically chemosensory cues, have been shown to guide therapeutic applications of medicinal plants. Humoral qualities, on the other hand, are widely believed to be an abstract concept, mainly applied post hoc to validate therapy. However, the nexus between humoral qualities, chemosensory properties, and medicinal plant uses has never been systematically assessed. To systematically analyse the correlations between chemosensory properties, humoral qualities, and medicinal uses of selected botanical drugs. The issue was approached experimentally via an organoleptic testing panel, consisting of Zoque healers in Chiapas, Mexico. The healers smelled and tasted 71 selected herbal drugs and subsequently commented on their humoral qualities and therapeutic uses. The resulting dataset is analysed for correlations between these variables using Bayesian statistics. Qualitative data on the characteristics and role of the hot-cold dichotomy complement the quan...
The precise knowledge of age is necessary for assessing a child's nutritional status. We show... more The precise knowledge of age is necessary for assessing a child's nutritional status. We show the magnitude and the effects of age error in real and hypothetical situations, and discuss possible compensative strategies. Using data collected in different years, we found that 79.8% of 1056 Ugandan children had some age knowledge, but there was a mean shift of 7.5 (±8.8) months between ages obtained from different sources. Using a free software for calculating the effect of bias and random error, we showed the variation in malnutrition prevalence in hypothetical cases.
Parametric regression models are often not flexible enough to capture the true relationships as t... more Parametric regression models are often not flexible enough to capture the true relationships as they tend to rely on arbitrary identification assumptions. Using the UK Labor Force Survey, we estimate the causal effect of national minimum wage (NMW) increases on the probability of job entry and job exit by means of a non parametric Bayesian modelling approach known as Bayesian Additive Regression Trees (BART). This procedure is simple, flexible and it does not require ad-hoc assumptions about model fitting, number of covariates and how they interact. We find that the NMW exerts a positive and significant impact on both the probability of job entry and job exit. Although the magnitude of the effect on job entry is higher, the overall effect of NMW is ambiguous as there are lot of more employed workers. This can explain the insignificant effect found in the previous studies based on aggregate macroeconomic data. Furthermore, the causal effect of NMW is higher for young workers and in p...
This paper presents a step-by-step tutorial to estimate causal effects in PISA 2012 by means of a... more This paper presents a step-by-step tutorial to estimate causal effects in PISA 2012 by means of a nonparametric Bayesian modeling approach known as Bayesian Additive Regression Trees (BART), with an illustration of the causal impact of ICT on Spanish students' performance. The R code is explained in a way that can be easily applied to other similar studies. The application shows that, compared to more traditional methodologies, the BART approach is particularly useful when a high-dimensional set of confounding variables is considered as its results are not based on a sampling hypothesis. BART allows for the estimation of different interactive effects between the treatment variable and other covariates. BART models do not require the analyst to make explicit subjective decisions in which covariates must be included in the final models. This makes it an easy procedure to guide policy makers' decisions in different contexts
The gamma-aminobutyric acid type A (GABA(A)) receptor is an important pharmacological target of e... more The gamma-aminobutyric acid type A (GABA(A)) receptor is an important pharmacological target of ethanol. The effect of ethanol withdrawal on the expression of the alpha(2) subunit of this receptor was examined with rat cerebellar granule cells in primary culture. Long-term exposure of these cells to ethanol (100 mM, 5 days) did not affect the abundance of the mRNA for the alpha(2) subunit, as revealed by an RNase protection assay. In contrast, subsequent ethanol withdrawal for 3 h induced a marked increase in the amount of this mRNA (2.6-fold) as well as in that of the encoded polypeptide (2.2-fold), the latter revealed by immunoblot analysis. Exposure of the cells to gamma-hydroxybutyric acid (100 mM) during ethanol withdrawal prevented the increase in the amounts of both the alpha(2) mRNA and polypeptide, whereas similar treatment with diazepam (10 microM) blocked the increase in the abundance of the alpha(2) polypeptide but not that in the amount of the alpha(2) mRNA. The effect ...
This work proposes a semi-parametric approach to estimate the evolution of COVID-19 (SARS-CoV-2) ... more This work proposes a semi-parametric approach to estimate the evolution of COVID-19 (SARS-CoV-2) in Spain. Considering the sequences of 14-day cumulative incidence of all Spanish regions, it combines modern Deep Learning (DL) techniques for analyzing sequences with the usual Bayesian Poisson-Gamma model for counts. The DL model provides a suitable description of the observed time series of counts, but it cannot give a reliable uncertainty quantification. The role of expert elicitation of the expected number of counts and its reliability is DL predictions’ role in the proposed modelling approach. Finally, the posterior predictive distribution of counts is obtained in a standard Bayesian analysis using the well known Poisson-Gamma model. The model allows to predict the future evolution of the sequences on all regions or estimates the consequences of eventual scenarios.
The variable selection problem in general, and specifically for the ordinary linear regression mo... more The variable selection problem in general, and specifically for the ordinary linear regression model, is considered in the setup in which the number of covariates is large enough to prevent the exploration of all possible models. In this context, Gibbs-sampling is needed to perform stochastic model exploration to estimate, for instance, the model inclusion probability. We show that under a Bayesian non-parametric prior model for analyzing Gibbs-sampling output, the usual empirical estimator is just the asymptotic version of the expected posterior inclusion probability given the simulation output from Gibbs-sampling. Other posterior conditional estimators of inclusion probabilities can also be considered as related to the latent probabilities distributions on the model space which can be sampled given the observed Gibbs-sampling output. This paper will also compare, in this large model space setup the conventional prior approach against the non-local prior approach used to define the...
Caves are an extreme environment for humans because of the high humidity, mud, darkness, and slip... more Caves are an extreme environment for humans because of the high humidity, mud, darkness, and slippery conditions. Explorations can last many hours or even days, and require extensive climbing and ropework. Very little is known about the physical capacity of cavers and their energy expenditure (EE) during caving. The physical capacity of 17 (7 females) expert cavers (age 43.9 ± 7.3 years) was assessed during an incremental cycle-ergometer test (IET) with gas exchange analysis. Moreover, a wearable metabolic band (Armband Fit Core) was used to estimate their EE during caving. In terms of physical capacity, the IET showed that cavers had a maximum oxygen uptake (VO) of 2,248.7 ± 657.8 ml·min(i.e., 32.4 ± 6.4 ml·kg·min), while anaerobic threshold (AT) occurred on average at 74.5% of VO. Results from caving sessions provided an average time spent in cave of 9.4 ± 1.2 h while the average EE was 268.8 ± 54.8 kcal·h, which corresponded to about 40% of VOmeasured during IET. A mean distance ...
Economics: The Open-Access, Open-Assessment E-Journal
Parametric regression models are often not flexible enough to capture the true relationships as t... more Parametric regression models are often not flexible enough to capture the true relationships as they tend to rely on arbitrary identification assumptions. Using the UK Labor Force Survey, the authors estimate the causal effect of national minimum wage (NMW) increases on the probability of job entry and job exit by means of a non-parametric Bayesian modelling approach known as Bayesian Additive Regression Trees (BART). The application of this methodology has the important advantage that it does not require ad-hoc assumptions about model fitting, number of covariates and how they interact. They find that the NMW exerts a positive and significant impact on both the probability of job entry and job exit. Although the magnitude of the effect on job entry is higher, the overall effect of NMW is ambiguous as there are many more employed workers. The causal effect of NMW is higher for young workers and in periods of high unemployment and they have a stronger impact on job entry decisions. N...
Organoleptic properties, and more specifically chemosensory cues, have been shown to guide therap... more Organoleptic properties, and more specifically chemosensory cues, have been shown to guide therapeutic applications of medicinal plants. Humoral qualities, on the other hand, are widely believed to be an abstract concept, mainly applied post hoc to validate therapy. However, the nexus between humoral qualities, chemosensory properties, and medicinal plant uses has never been systematically assessed. To systematically analyse the correlations between chemosensory properties, humoral qualities, and medicinal uses of selected botanical drugs. The issue was approached experimentally via an organoleptic testing panel, consisting of Zoque healers in Chiapas, Mexico. The healers smelled and tasted 71 selected herbal drugs and subsequently commented on their humoral qualities and therapeutic uses. The resulting dataset is analysed for correlations between these variables using Bayesian statistics. Qualitative data on the characteristics and role of the hot-cold dichotomy complement the quan...
The precise knowledge of age is necessary for assessing a child's nutritional status. We show... more The precise knowledge of age is necessary for assessing a child's nutritional status. We show the magnitude and the effects of age error in real and hypothetical situations, and discuss possible compensative strategies. Using data collected in different years, we found that 79.8% of 1056 Ugandan children had some age knowledge, but there was a mean shift of 7.5 (±8.8) months between ages obtained from different sources. Using a free software for calculating the effect of bias and random error, we showed the variation in malnutrition prevalence in hypothetical cases.
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Papers by Stefano Cabras