Determinants of WTP for Prosecco wine: A latent class regression with attitudinal responses

Purpose – Under investigation is Prosecco wine, a sparkling white wine from North-East Italy.
Information collection on consumer perceptions is particularly relevant when developing market
strategies for wine, especially so when local production and certification of origin play an important
role in the wine market of a given district, as in the case at hand. Investigating and characterizing the
structure of preference heterogeneity become crucial steps in every successful marketing strategy. The
purpose of this paper is to investigate the sources of systematic differences in consumer preferences.
Design/methodology/approach – The paper explores the effect of inclusion of answers to
attitudinal questions in a latent class regression model of stated willingness to pay (WTP) for this
specialty wine. These additional variables were included in the membership equations to investigate
whether they could be of help in the identification of latent classes. The individual specific WTPs from
the sampled respondents were then derived from the best fitting model and examined for consistency.
Findings – The use of answers to attitudinal question in the latent class regression model is found to
improve model fit, thereby helping in the identification of latent classes. The best performing model
obtained makes use of both attitudinal scores and socio-economic covariates identifying five latent
classes. A reasonable pattern of differences in WTP for Prosecco between CDO and TGI types were
derived from this model.
Originality/value – The approach appears informative and promising: attitudes emerge as
important ancillary indicators of taste differences for specialty wines. This might be of interest per se
and of practical use in market segmentation. If future research shows that these variables can be of use
in other contexts, it is quite possible that more attitudinal questions will be routinely incorporated in
structural latent class hedonic models.

PREDICTING THE SPATIAL-DISTRIBUTION OF CLIMATE - TEMPERATURE IN GREAT-BRITAIN

1. The prediction and mapping of climate in areas between climate stations is of increasing importance in ecology.

2. Four categories of model, simple interpolation, thin plate splines, multiple linear regression and mixed spline-regression, were tested for their ability to predict the spatial distribution of temperature on the British mainland. The models were tested by external cross-verification.

3. The British distribution of mean daily temperature was predicted with the greatest accuracy by using a mixed model: a thin plate spline fitted to the surface of the country, after correction of the data by a selection from 16 independent topographical variables (such as altitude, distance from the sea, slope and topographic roughness), chosen by multiple regression from a digital terrain model (DTM) of the country.

4. The next most accurate method was a pure multiple regression model using the DTM. Both regression and thin plate spline models based on a few variables (latitude, longitude and altitude) only were comparatively unsatisfactory, but some rather simple methods of surface interpolation (such as bilinear interpolation after correction to sea level) gave moderately satisfactory results. Differences between the methods seemed to be dependent largely on their ability to model the effect of the sea on land temperatures.

5. Prediction of temperature by the best methods was greater than 95% accurate in all months of the year, as shown by the correlation between the predicted and actual values. The predicted temperatures were calculated at real altitudes, not subject to sea-level correction.

6. A minimum of just over 30 temperature recording stations would generate a satisfactory surface, provided the stations were well spaced.

7. Maps of mean daily temperature, using the best overall methods are provided; further important variables, such as continentality and length of growing season, were also mapped. Many of these are believed to be the first detailed representations at real altitude.

8. The interpolated monthly temperature surfaces are available on disk.

The Cyclin D1 (CCND1) A870G polymorphism predicts clinical outcome to lapatinib and capecitabine in HER2-positive metastatic breast cancer

BACKGROUND: Lapatinib plus capecitabine emerged as an efficacious therapy in metastatic breast cancer (mBC). We aimed to identify germline single-nucleotide polymorphisms (SNPs) in genes involved in capecitabine catabolism and human epidermal receptor signaling that were associated with clinical outcome to assist in selecting patients likely to benefit from this combination.

PATIENTS AND METHODS: DNA was extracted from 240 of 399 patients enrolled in EGF100151 clinical trial (NCT00078572; clinicaltrials.gov) and SNPs were successfully evaluated in 234 patients. The associations between SNPs and clinical outcome were analyzed using Fisher's exact test, Kaplan-Meier curves, log-rank tests, likelihood ratio test within logistic or Cox regression model, as appropriate.

RESULTS: There were significant interactions between CCND1 A870G and clinical outcome. Patients carrying the A-allele were more likely to benefit from lapatinib plus capecitabine versus capecitabine when compared with patients harboring G/G (P = 0.022, 0.024 and 0.04, respectively). In patients with the A-allele, the response rate (RR) was significantly higher with lapatinib plus capecitabine (35%) compared with capecitabine (11%; P = 0.001) but not between treatments in patients with G/G (RR = 24% and 32%, respectively; P = 0.85). Time to tumor progression (TTP) was longer in patients with the A-allele treated with lapatinib plus capecitabine compared with capecitabine (median TTP = 7.9 and 3.4 months; P < 0.001), but not in patients with G/G (median TTP = 6.1 and 6.6 months; P = 0.92).

CONCLUSION: Our findings suggest that CCND1A870G may be useful in predicting clinical outcome in HER2-positive mBC patients treated with lapatinib plus capecitabine.

Heller's myotomy and pneumatic dilatation in the treatment of achalasia: a population-based case–control study assessing long-term quality of life

Long-term health-related quality-of-life (HRQL) outcomes have not been widely reported in the
treatment of achalasia. The aims of this study were to examine long-term disease-specific and general HRQL in
achalasia patients using a population-based case–control method, and to assess HRQL between treatment interventions.
Manometrically diagnosed achalasia cases (n = 120) were identified and matched with controls (n = 115)
using a population-based approach. Participants completed general (SF-12) and disease-specific (Achalasia Severity
Questionnaire [ASQ]) HRQL questionnaires, as appropriate, in a structured interview. Mean composite scores
for SF-12 (Mental Component Summary score [MCS-12] and Physical Component Summary score [PCS-12]) and
ASQ were compared between cases and controls, or between intervention groups, using an independent t-test.
Adjusted mean differences in HRQL scores were evaluated using a linear regression model. Achalasia cases were
treated with a Heller’s myotomy (n = 43), pneumatic dilatation (n = 44), or both modalities (n = 33). The median
time from last treatment to HRQL assessment was 5.7 years (interquartile range 2.4–11.5). Comparing achalasia
patients with controls, PCS-12 was significantly worse (40.9 vs. 44.2, P = 0.01), but MCS-12 was similar. However,
both PCS-12 (39.9 vs. 44.2, P = 0.03) and MCS-12 (46.7 vs. 53.5, P = 0.004) were significantly impaired in those
requiring dual treatment compared with controls. Overall however, there was no difference in adjusted HRQL
between patients treated with Heller’s myotomy, pneumatic dilatation or both treatment modalities. In summary,
despite treatment achalasia patients have significantly worse long-term physical HRQL compared with population
controls. No HRQL differences were observed between the treatment modalities to suggest a benefit of one
treatment over another.

Validating the accuracy of a model to predict the onset of myopia in children.

PURPOSE: To assess the sensitivity and specificity of models predicting myopia onset among ethnically Chinese children. METHODS: Visual acuity, height, weight, biometry (A-scan, keratometry), and refractive error were assessed at baseline and 3 years later using the same equipment and protocol in primary schools in Xiamen (China) and Singapore. A regression model predicting the onset of myopia < -0.75 diopters (D) after 3 years in either eye among Xiamen children was validated with Singapore data. RESULTS: Baseline data were collected from 236 Xiamen children (mean age, 7.82 ± 0.63 years) and from 1979 predominantly Chinese children in Singapore (7.83 ± 0.84 years). Singapore children were significantly taller and heavier, and had more myopia (31.4% vs. 6.36% < -0.75 D in either eye, P < 0.001) and longer mean axial length. Three-year follow-up was available for 80.0% of Xiamen children and 83.1% in Singapore. For Xiamen, the area under the receiver-operator curve (AUC) in a model including ocular biometry, height, weight, and presenting visual acuity was 0.974 (95% confidence interval [CI], 0.945-0.997). In Singapore, the same model achieved sensitivity, specificity, and positive predictive value of 0.844, 0.650, and 0.669, with an AUC of 0.815 (95% CI, 0.791-0.839). CONCLUSIONS: Accuracy in predicting myopia onset based on simple measurements may be sufficient to make targeted early intervention practical in settings such as Singapore with high myopia prevalence. Models based on cohorts with a greater prevalence of high myopia than that in Xiamen could be used to assess accuracy of models predicting more severe forms of myopia.

Associates of an elevated natriuretic peptide level in stable heart failure patients:implications for targeted management

BACKGROUND: Persistently elevated natriuretic peptide (NP) levels in heart failure (HF) patients are associated with impaired prognosis. Recent work suggests that NP-guided therapy can improve outcome, but the mechanisms behind an elevated BNP remain unclear. Among the potential stimuli for NP in clinically stable patients are persistent occult fluid overload, wall stress, inflammation, fibrosis, and ischemia. The purpose of this study was to identify associates of B-type natriuretic peptide (BNP) in a stable HF population.

METHODS: In a prospective observational study of 179 stable HF patients, the association between BNP and markers of collagen metabolism, inflammation, and Doppler-echocardiographic parameters including left ventricular ejection fraction (LVEF), left atrial volume index (LAVI), and E/e prime (E/e') was measured.

RESULTS: Univariable associates of elevated BNP were age, LVEF, LAVI, E/e', creatinine, and markers of collagen turnover. In a multiple linear regression model, age, creatinine, and LVEF remained significant associates of BNP. E/e' and markers of collagen turnover had a persistent impact on BNP independent of these covariates.

CONCLUSION: Multiple variables are associated with persistently elevated BNP levels in stable HF patients. Clarification of the relative importance of NP stimuli may help refine NP-guided therapy, potentially improving outcome for this at-risk population.

Do Total and High Density Lipoprotein Cholesterol and Triglycerides Act Independently in the Prediction of Ischemic Heart Disease? Ten-Year Follow-Up of Caerphilly and Speedwell Cohorts

Several studies have suggested that men with raised plasma triglycerides (TGs) in combination with adverse levels of other lipids may be at special risk of subsequent ischemic heart disease (IHD). We examined the independent and combined effects of plasma lipids at 10 years of follow-up. We measured fasting TGs, total cholesterol (TC), and high density lipoprotein cholesterol (HDLC) in 4362 men (aged 45 to 63 years) from 2 study populations and reexamined them at intervals during a 10-year follow-up. Major IHD events (death from IHD, clinical myocardial infarction, or ECG-defined myocardial infarction) were recorded. Five hundred thirty-three major IHD events occurred. All 3 lipids were strongly and independently predictive of IHD after 10 years of follow-up. Subjects were then divided into 27 groups (ie, 33) by the tertiles of TGs, TC, and HDLC. The number of events observed in each group was compared with that predicted by a logistic regression model, which included terms for the 3 lipids (without interactions) and potential confounding variables. The incidence of IHD was 22.6% in the group with the lipid risk factor combination with the highest expected risk (high TGs, high TC, and low HDLC) and 4.7% in the group with the lowest expected risk (P

Dynamic Multivariate Statistical Process Control using Subspace Identification

This paper points out a serious flaw in dynamic multivariate statistical process control (MSPC). The principal component analysis of a linear time series model that is employed to capture auto- and cross-correlation in recorded data may produce a considerable number of variables to be analysed. To give a dynamic representation of the data (based on variable correlation) and circumvent the production of a large time-series structure, a linear state space model is used here instead. The paper demonstrates that incorporating a state space model, the number of variables to be analysed dynamically can be considerably reduced, compared to conventional dynamic MSPC techniques.

Further assessment of the complement component 2 and factor B region associated with age-related macular degeneration

PURPOSE. Polymorphic variation in genes involved in regulation of the complement system has been implicated as a major cause of genetic risk, in addition to the LOC387715/HTRA1 locus and other environmental influences. Previous studies have identified polymorphisms in the complement component 2 (CC2) and factor B (CFB) genes, as potential functional variants associated with AMD, in particular CFB R32Q and CC2 rs547154, both of which share strong linkage disequilibrium (LD). METHODS. Data derived from the HapMap Project were used to select 18 haplotype-tagging SNPs across the extended CC2/ CFB region for genotyping, to measure the strength of LD in 318 patients with neovascular AMD and 243 age-matched control subjects to identify additional potential functional variants in addition to those originally reported. RESULTS. Strong LD was measured across this region as far as the superkiller viralicidic activity 2-like gene (SKIV2L). Nine SNPs were identified to be significantly associated with the genetic effect observed at this locus. Of these, a nonsynonymous coding variant SKIV2L R151Q (rs438999; OR, 0.48; 95% confidence interval [CI], 0.31- 0.74; P < 0.001), was in strong LD with CFB R32Q, rs641153 (r2 = 0.95) and may exert a functional effect. When assessed within a logistic regression model measuring the effects of genetic variation at the CFH and LOC387715/HTRA1 loci and smoking, the effect remained significant (OR, 0.38; 95% CI, 0.22- 0.65; P < 0.001). Additional variation identified within this region may also confer a weaker but independent effect and implicate additional genes within the pathogenesis of AMD. CONCLUSIONS. Because of the high level of LD within the extended CC2/CFB region, variation within SKIV2L may exert a functional effect in AMD. Copyright © Association for Research in Vision and Ophthalmology.

Does governance matter for aggregate health capital?

The point of departure of our analysis is the seminal work of Rodgers (1979) on the absolute and relative income hypotheses. We find that substituting the governance index for the Gini index is statistically the preferred regression model. Our findings lend support to the argument that governance matters. Further investigation provides evidence for two types of threshold effects: in terms of both absolute income and governance. For those countries below a threshold, absolute income is the most significant determinant of health, while for those above it, governance matters the most. The regression analyses are conducted on a sample of 112 states, which is representative of a wide range of absolute income and governance levels.

A hierarchical multiclass support vector machine incorporated with holistic triple learning units

This paper proposes a new hierarchical learning structure, namely the holistic triple learning (HTL), for extending the binary support vector machine (SVM) to multi-classification problems. For an N-class problem, a HTL constructs a decision tree up to a depth of A leaf node of the decision tree is allowed to be placed with a holistic triple learning unit whose generalisation abilities are assessed and approved. Meanwhile, the remaining nodes in the decision tree each accommodate a standard binary SVM classifier. The holistic triple classifier is a regression model trained on three classes, whose training algorithm is originated from a recently proposed implementation technique, namely the least-squares support vector machine (LS-SVM). A major novelty with the holistic triple classifier is the reduced number of support vectors in the solution. For the resultant HTL-SVM, an upper bound of the generalisation error can be obtained. The time complexity of training the HTL-SVM is analysed, and is shown to be comparable to that of training the one-versus-one (1-vs.-1) SVM, particularly on small-scale datasets. Empirical studies show that the proposed HTL-SVM achieves competitive classification accuracy with a reduced number of support vectors compared to the popular 1-vs-1 alternative.

Six ways to leave unemployment

This paper uses a unique Portuguese dataset to examine the effect of access to unemployment benefits (UBs) and their maximum potential duration on escape rates from unemployment. In examining the time profile of transitions out of unemployment, the principal contributions of the paper are twofold. First, it provides a detailed state space of potential outcomes: open-ended employment, fixed-term contracts, part-time work, government-provided jobs, self employment, and labour force withdrawal. Second, it is able to exploit major exogenous discontinuities in the maximum duration of unemployment benefits to identify disincentive effects. While confirming strong disincentive effects, it is shown that use of an aggregate hazard function regression model compounds very different and even contradictory effects of the determinants of unemployment.

Climate change-linked range expansion of Nathusius' pipistrelle bat, Pipistrellus nathusii (Keyserling & Blasius, 1839)

Aim To examine the effect of climate change on the occurrence and distribution of Pipistrellus nathusii (Nathusius' pipistrelle) in the United Kingdom (UK).Location We modelled habitat and climatic associations of P. nathusii in the UK and applied this model to the species' historical range in continental Europe.Methods A binomial logistic regression model was constructed relating the occurrence of P. nathusii to climate and habitat characteristics using historical species occurrence records (1940-2006) and CORINE land cover data. This model was applied to historical and projected climate data to examine changes in suitable range (1940-2080) of this species. We tested the predictive ability of the model with known records in the UK after 2006 and applied the model to the species' known range in Europe.Results The distribution of P. nathusii was related positively to the area of water bodies, woodland and small areas of urbanization, and negatively related to the area of peat/heathland. Species records were associated with higher minimum temperatures, low seasonal variation in temperature and intermediate rainfall. We found that suitable areas have existed in the UK since the 1940s and that these have expanded. The model had high predictive power when applied to new records after 2006, with a correct classification rate of 70%, estimated by receiver operating characteristic analysis. Based on climate projections, our model suggests a potential twofold increase in the area suitable for P. nathusii in the UK by 2050. The single most influential climate variable contributing to range increase was the projected increase in minimum temperature. When applied to Europe, the model predictions had best predictive capability of known records in western areas of the species' range, where P. nathusii is present during the winter.Main conclusions We show that a mobile, migratory species has adapted its range in response to recent climate change on a continental scale. We believe this may be the first study to demonstrate a case of range change linked to contemporary climate change in a mammal species in Europe.

Impaired endothelium-dependent vasodilatation is a novel predictor of mortality in intensive care

Objective: Endothelial function may be impaired in critical illness. We hypothesized that impaired endothelium-dependent vasodilatation is a predictor of mortality in critically ill patients.
Design: Prospective observational cohort study.
Setting: Seventeen-bed adult intensive care unit in a tertiary referral university teaching hospital. Patients: Patients were recruited within 24 hrs of admission to the intensive care unit.
Interventions: The SphygmoCor Mx system was used to derive the aortic augmentation index from radial artery pulse pressure waveforms. Endothelium-dependent vasodilatation was calculated as the change in augmentation index in response to an endothelium-dependent vasodilator (salbutamol).
Measurements and Main Results: Demographics, severity of illness scores, and physiological parameters were collected. Statistically significant predictors of mortality identified using single regressor analysis were entered into a multiple logistic regression model. Receiver operator characteristic curves were generated. Ninety-four patients completed the study. There were 80 survivors and 14 nonsurvivors. The Simplified Acute Physiology Score II, the Sequential Organ Failure Assessment score, leukocyte count, and endothelium-dependent vasodilatation conferred an increased risk of mortality. In logistic regression analysis, endothelium-dependent vasodilatation was the only predictor of mortality with an adjusted odds ratio of 26.1 (95% confidence interval [CI], 4.3-159.5). An endothelium-dependent vasodilatation value of 0.5% or less predicted intensive care unit mortality with a sensitivity of 79% (CI, 59-88%) and specificity of 98% (CI, 94-99%).
Conclusions: In vivo bedside assessment of endothelium-dependent vasodilatation is an independent predictor of mortality in the critically ill. We have shown it to be superior to other validated severity of illness scores with high sensitivity and specificity.

School Neighborhood Disadvantage as a Predictor of Long-Term Sick Leave Among Teachers: Prospective Cohort Study

This ongoing prospective study examined characteristics of school neighborhood and neighborhood of residence as predictors of sick leave among school teachers. School neighborhood income data for 226 lower-level comprehensive schools in 10 towns in Finland were derived from Statistics Finland and were linked to register-based data on 3,063 teachers with no long-term sick leave at study entry. Outcome was medically certified (> 9 days) sick leave spells during a mean follow-up of 4.3 years from data collection in 2000-2001. A multilevel, cross-classified Poisson regression model, adjusted for age, type of teaching job, length and type of job contract, school size, baseline health status, and income level of the teacher's residential area, showed a rate ratio of 1.30 (95% confidence interval: 1.03, 1.63) for sick leave among female teachers working in schools located in low-income neighborhoods compared with those working in high-income neighborhoods. A low income level of the teacher's residential area was also independently associated with sick leave among female teachers (rate ratio = 1.50, 95% confidence interval: 1.18, 1.91). Exposure to both low-income school neighborhoods and low-income residential neighborhoods was associated with the greatest risk of sick leave (rate ratio = 1.71, 95% confidence interval: 1.27, 2.30). This study indicates that working and living in a socioeconomically disadvantaged neighborhood is associated with increased risk of sick leave among female teachers.