USING ORDER STATISTICS TO ESTIMATE PROBABILITIES OF PURCHASE FOR CONSUMER GOODS

Much work has been done recently to develop models of individual brand choice. This work has been especially fruitful in the area of “attribute investigation” (e.g., conjoint analysis) for the purpose of uncovering an “ideal” set of product attributes for a given product on a customer-by-customer basis. These techniques have been employed in several strategic areas of marketing, including product specification, pricing, service prioritization, brand image/equity, and satisfaction/loyalty. Similarly, some effort has been made with the issue of optimal advertising strategy. This paper considers the advertising effectiveness function within the context of other interrelated variables such as consumer preference (brand choice) for a brand vis-à-vis its competitors. The model suggests, among other things, that under certain reasonable conditions, the advertising response function may not be “diminishing marginal returns” or ‘S-shaped’ as is usually assumed, but instead will increase up to a point and then decline. The model also explicitly considers the advertising expenditures of competing brands, as well as intrinsic "liking" for them. The consideration of competitive activity, in the present study may yield a more complete model of advertising response than is found elsewhere. Finally the model provides direction for strategic purposes in its ability to illustrate in a fairly straightforward and graphical sense how advertising and promotion “work” in much the same way that demand and supply curves illustrate how the various economic inputs work.Statistics Working Papers Serie

SOLVING A CLASS OF TRAVELING SALESMAN PROBLEMS ANALYTICALLY

This paper addresses a class of Traveling Salesman Problems (TSP) in which a route must be made to a series of nodes and return to the original location and attempts to solve it using analytical methods. The problem will be presented as a matrix of routes, much as might be seen in a national road map, excepting for there being in this case less entries. This familiar arrangement of routes will be cast as a matrix problem and solved using familiar formulations of quadratic forms. This solution, should it prove successful, can be contrasted with differing numeric or even iterative methods, such as the well-known Gomory cut method of solving integer linear programs. The advantage, should it prove tenable, will be theoretic in that a familiar and accessible form of quadratic forms can be readily applied to the problem and to similar cases.Statistics Working Papers Serie

USING ORDER STATISTICS TO ESTIMATE PROBABILITIES OF PURCHASE FOR CONSUMER GOODS

Much work has been done recently to develop models of individual brand choice. This work has been especially fruitful in the area of “attribute investigation” (e.g., conjoint analysis) for the purpose of uncovering an “ideal” set of product attributes for a given product on a customer-by-customer basis. These techniques have been employed in several strategic areas of marketing, including product specification, pricing, service prioritization, brand image/equity, and satisfaction/loyalty. Similarly, some effort has been made with the issue of optimal advertising strategy. This paper considers the advertising effectiveness function within the context of other interrelated variables such as consumer preference (brand choice) for a brand vis-à-vis its competitors. The model suggests, among other things, that under certain reasonable conditions, the advertising response function may not be “diminishing marginal returns” or ‘S-shaped’ as is usually assumed, but instead will increase up to a point and then decline. The model also explicitly considers the advertising expenditures of competing brands, as well as intrinsic "liking" for them. The consideration of competitive activity, in the present study may yield a more complete model of advertising response than is found elsewhere. Finally the model provides direction for strategic purposes in its ability to illustrate in a fairly straightforward and graphical sense how advertising and promotion “work” in much the same way that demand and supply curves illustrate how the various economic inputs work.Statistics Working Papers Serie

Patient-directed self-management of pain (PaDSMaP) compared to treatment as usual following total knee replacement; a randomised controlled trial

Background Self-administration of medicines by patients whilst in hospital is being increasingly promoted despite little evidence to show the risks and benefits. Pain control after total knee replacement (TKR) is known to be poor. The aim of the study was to determine if patients operated on with a TKR who self-medicate their oral analgesics in the immediate post-operative period have better pain control than those who receive their pain control by nurse-led drug rounds (Treatment as Usual (TAU)). Methods A prospective, parallel design, open-label, randomised controlled trial comparing pain control in patient-directed self-management of pain (PaDSMaP) with nurse control of oral analgesia (TAU) after a TKR. Between July 2011 and March 2013, 144 self-medicating adults were recruited at a secondary care teaching hospital in the UK. TAU patients (n = 71) were given medications by a nurse after their TKR. PaDSMaP patients (n = 73) took oral medications for analgesia and co-morbidities after two 20 min training sessions reinforced with four booklets. Primary outcome was pain (100 mm visual analogue scale (VAS)) at 3 days following TKR surgery or at discharge (whichever came soonest). Seven patients did not undergo surgery for reasons unrelated to the study and were excluded from the intention-to-treat (ITT) analysis. Results ITT analysis did not detect any significant differences between the two groups’ pain scores. A per protocol (but underpowered) analysis of the 60% of patients able to self-medicate found reduced pain compared to the TAU group at day 3/discharge, (VAS -9.9 mm, 95% CI -18.7, − 1.1). One patient in the self-medicating group over-medicated but suffered no harm. Conclusion Self-medicating patients did not have better (lower) pain scores compared to the nurse-managed patients following TKR. This cohort of patients were elderly with multiple co-morbidities and may not be the ideal target group for self-medication

Common Genetic Polymorphisms Influence Blood Biomarker Measurements in COPD

Implementing precision medicine for complex diseases such as chronic obstructive lung disease (COPD) will require extensive use of biomarkers and an in-depth understanding of how genetic, epigenetic, and environmental variations contribute to phenotypic diversity and disease progression. A meta-analysis from two large cohorts of current and former smokers with and without COPD [SPIROMICS (N = 750); COPDGene (N = 590)] was used to identify single nucleotide polymorphisms (SNPs) associated with measurement of 88 blood proteins (protein quantitative trait loci; pQTLs). PQTLs consistently replicated between the two cohorts. Features of pQTLs were compared to previously reported expression QTLs (eQTLs). Inference of causal relations of pQTL genotypes, biomarker measurements, and four clinical COPD phenotypes (airflow obstruction, emphysema, exacerbation history, and chronic bronchitis) were explored using conditional independence tests. We identified 527 highly significant (p 10% of measured variation in 13 protein biomarkers, with a single SNP (rs7041; p = 10−392) explaining 71%-75% of the measured variation in vitamin D binding protein (gene = GC). Some of these pQTLs [e.g., pQTLs for VDBP, sRAGE (gene = AGER), surfactant protein D (gene = SFTPD), and TNFRSF10C] have been previously associated with COPD phenotypes. Most pQTLs were local (cis), but distant (trans) pQTL SNPs in the ABO blood group locus were the top pQTL SNPs for five proteins. The inclusion of pQTL SNPs improved the clinical predictive value for the established association of sRAGE and emphysema, and the explanation of variance (R2) for emphysema improved from 0.3 to 0.4 when the pQTL SNP was included in the model along with clinical covariates. Causal modeling provided insight into specific pQTL-disease relationships for airflow obstruction and emphysema. In conclusion, given the frequency of highly significant local pQTLs, the large amount of variance potentially explained by pQTL, and the differences observed between pQTLs and eQTLs SNPs, we recommend that protein biomarker-disease association studies take into account the potential effect of common local SNPs and that pQTLs be integrated along with eQTLs to uncover disease mechanisms. Large-scale blood biomarker studies would also benefit from close attention to the ABO blood group