Application of multivariate statistical process control to fuel cell manufacturing

Univariate statistical control charts, such as the Shewhart chart, do not satisfy the requirements for process monitoring on a high volume automated fuel cell manufacturing line. This is because of the number of variables that require monitoring. The risk of elevated false alarms, due to the nature of the process being high volume, can present problems if univariate methods are used. Multivariate statistical methods are discussed as an alternative for process monitoring and control. The research presented is conducted on a manufacturing line which evaluates the performance of a fuel cell. It has three stages of production assembly that contribute to the final end product performance. The product performance is assessed by power and energy measurements, taken at various time points throughout the discharge testing of the fuel cell. The literature review performed on these multivariate techniques are evaluated using individual and batch observations. Modern techniques using multivariate control charts on Hotellings T2 are compared to other multivariate methods, such as Principal Components Analysis (PCA). The latter, PCA, was identified as the most suitable method. Control charts such as, scores, T2 and DModX charts, are constructed from the PCA model. Diagnostic procedures, using Contribution plots, for out of control points that are detected using these control charts, are also discussed. These plots enable the investigator to perform root cause analysis. Multivariate batch techniques are compared to individual observations typically seen on continuous processes. Recommendations, for the introduction of multivariate techniques that would be appropriate for most high volume processes, are also covered.

Modelling dependence in a ratemaking procedure with multivariate Poisson regression models

When actuaries face with the problem of pricing an insurance contract that contains different types of coverage, such as a motor insurance or homeowner's insurance policy, they usually assume that types of claim are independent. However, this assumption may not be realistic: several studies have shown that there is a positive correlation between types of claim. Here we introduce different regression models in order to relax the independence assumption, including zero-inflated models to account for excess of zeros and overdispersion. These models have been largely ignored to multivariate Poisson date, mainly because of their computational di±culties. Bayesian inference based on MCMC helps to solve this problem (and also lets us derive, for several quantities of interest, posterior summaries to account for uncertainty). Finally, these models are applied to an automobile insurance claims database with three different types of claims. We analyse the consequences for pure and loaded premiums when the independence assumption is relaxed by using different multivariate Poisson regression models and their zero-inflated versions.

Policy Credibility and Delegation to Independent Regulatory Agencies: A Comparative Empirical Analysis

Independent regulatory agencies are one of the main institutional features of the 'rising regulatory state' in Western Europe. Governments are increasingly willing to abandon their regulatory competencies and to delegate them to specialized institutions that are at least partially beyond their control. This article examines the empirical consistency of one particular explanation of this phenomenon, namely the credibility hypothesis, claiming that governments delegate powers so as to enhance the credibility of their policies. Three observable implications are derived from the general hypothesis, linking credibility and delegation to veto players, complexity and interdependence. An independence index is developed to measure agency independence, which is then used in a multivariate analysis where the impact of credibility concerns on delegation is tested. The analysis relies on an original data set comprising independence scores for thirty-three regulators. Results show that the credibility hypothesis can explain a good deal of the variation in delegation. The economic nature of regulation is a strong determinant of agency independence, but is mediated by national institutions in the form of veto players.

Multivariate QST-FST comparisons: a neutrality test for the evolution of the g matrix in structured populations.

Neutrality tests in quantitative genetics provide a statistical framework for the detection of selection on polygenic traits in wild populations. However, the existing method based on comparisons of divergence at neutral markers and quantitative traits (Q(st)-F(st)) suffers from several limitations that hinder a clear interpretation of the results with typical empirical designs. In this article, we propose a multivariate extension of this neutrality test based on empirical estimates of the among-populations (D) and within-populations (G) covariance matrices by MANOVA. A simple pattern is expected under neutrality: D = 2F(st)/(1 - F(st))G, so that neutrality implies both proportionality of the two matrices and a specific value of the proportionality coefficient. This pattern is tested using Flury's framework for matrix comparison [common principal-component (CPC) analysis], a well-known tool in G matrix evolution studies. We show the importance of using a Bartlett adjustment of the test for the small sample sizes typically found in empirical studies. We propose a dual test: (i) that the proportionality coefficient is not different from its neutral expectation [2F(st)/(1 - F(st))] and (ii) that the MANOVA estimates of mean square matrices between and among populations are proportional. These two tests combined provide a more stringent test for neutrality than the classic Q(st)-F(st) comparison and avoid several statistical problems. Extensive simulations of realistic empirical designs suggest that these tests correctly detect the expected pattern under neutrality and have enough power to efficiently detect mild to strong selection (homogeneous, heterogeneous, or mixed) when it is occurring on a set of traits. This method also provides a rigorous and quantitative framework for disentangling the effects of different selection regimes and of drift on the evolution of the G matrix. We discuss practical requirements for the proper application of our test in empirical studies and potential extensions.

Atrial fibrillation and minimally invasive coronary artery bypass grafting: risk factor analysis.

Atrial fibrillation (AF) is a frequent arrhythmia after conventional coronary artery bypass grafting. With the advent of minimally invasive technique for left internal mammary artery-left anterior descending coronary artery (LIMA-LAD) grafting, we analyzed the incidence and the risk factors of postoperative AF in this patient population. This prospective study involves all patients undergoing isolated LIMA-LAD grafting with minimally invasive technique between January 1994 and June 2000. Twenty-four possible risk factors for postoperative AF were entered into univariate and multivariate logistic regression analyses. Postoperative AF occurred in 21 of the 90 patients (23.3%) analyzed. Double- or triple-vessel disease was present in 12/90 patients (13.3%). On univariate analysis, right coronary artery disease (p <0.01), age (p = 0.01), and diabetes (p = 0.04) were found to be risk factors for AF. On multivariate analysis, right coronary artery disease was identified as the sole significant risk factor (p = 0.02). In this patient population, the incidence of AF after minimally invasive coronary artery bypass is in the range of that reported for conventional coronary artery bypass grafting. Right coronary artery disease was found to be an independent predictor, and this may be related to the fact that in this patient population the diseased right coronary artery was not revascularized at the time of the surgical procedure. For the same reason, this risk factor may find a broader application to noncardiac thoracic surgery.

An R Library for Compositional Data Analysis in Archaeometry

Compositional data naturally arises from the scientific analysis of the chemicalcomposition of archaeological material such as ceramic and glass artefacts. Data of thistype can be explored using a variety of techniques, from standard multivariate methodssuch as principal components analysis and cluster analysis, to methods based upon theuse of log-ratios. The general aim is to identify groups of chemically similar artefactsthat could potentially be used to answer questions of provenance.This paper will demonstrate work in progress on the development of a documentedlibrary of methods, implemented using the statistical package R, for the analysis ofcompositional data. R is an open source package that makes available very powerfulstatistical facilities at no cost. We aim to show how, with the aid of statistical softwaresuch as R, traditional exploratory multivariate analysis can easily be used alongside, orin combination with, specialist techniques of compositional data analysis.The library has been developed from a core of basic R functionality, together withpurpose-written routines arising from our own research (for example that reported atCoDaWork'03). In addition, we have included other appropriate publicly availabletechniques and libraries that have been implemented in R by other authors. Availablefunctions range from standard multivariate techniques through to various approaches tolog-ratio analysis and zero replacement. We also discuss and demonstrate a smallselection of relatively new techniques that have hitherto been little-used inarchaeometric applications involving compositional data. The application of the libraryto the analysis of data arising in archaeometry will be demonstrated; results fromdifferent analyses will be compared; and the utility of the various methods discussed

Clinicopathologic analysis of acute myeloid leukemia arising from chronic myelomonocytic leukemia.

Acute myeloid leukemia arising from chronic myelomonocytic leukemia is currently classified as acute myeloid leukemia with myelodysplasia-related changes, a high-risk subtype. However, the specific features of these cases have not been well described. We studied 38 patients with chronic myelomonocytic leukemia who progressed to acute myeloid leukemia. We compared the clinicopathologic and genetic features of these cases with 180 patients with de novo acute myeloid leukemia and 34 patients with acute myeloid leukemia following myelodysplastic syndromes. We also examined features associated with progression from chronic myelomonocytic leukemia to acute myeloid leukemia by comparing the progressed chronic myelomonocytic leukemia cases with a cohort of chronic myelomonocytic leukemia cases that did not transform to acute myeloid leukemia. Higher white blood cell count, marrow cellularity, karyotype risk score, and Revised International Prognostic Scoring System score were associated with more rapid progression from chronic myelomonocytic leukemia to acute myeloid leukemia. Patients with acute myeloid leukemia ex chronic myelomonocytic leukemia were older (P<0.01) and less likely to receive aggressive treatment (P=0.02) than de novo acute myeloid leukemia patients. Most cases showed monocytic differentiation and fell into the intermediate acute myeloid leukemia karyotype risk group; 55% had normal karyotype and 17% had NPM1 mutation. Median overall survival was 6 months, which was inferior to de novo acute myeloid leukemia (17 months, P=0.002) but similar to post myelodysplastic syndrome acute myeloid leukemia. On multivariate analysis of all acute myeloid leukemia patients, only age and karyotype were independent prognostic variables for overall survival. Our findings indicate that acute myeloid leukemia following chronic myelomonocytic leukemia displays aggressive behavior and support placement of these cases within the category of acute myeloid leukemia with myelodysplasia-related changes. The poor prognosis of these patients may be related to an older population and lack of favorable-prognosis karyotypes that characterize many de novo acute myeloid leukemia cases.

Impact of inadequate empirical therapy on the mortality of patients with bloodstream infections: a propensity score-based analysis.

The impact of the adequacy of empirical therapy on outcome for patients with bloodstream infections (BSI) is key for determining whether adequate empirical coverage should be prioritized over other, more conservative approaches. Recent systematic reviews outlined the need for new studies in the field, using improved methodologies. We assessed the impact of inadequate empirical treatment on the mortality of patients with BSI in the present-day context, incorporating recent methodological recommendations. A prospective multicenter cohort including all BSI episodes in adult patients was performed in 15 hospitals in Andalucía, Spain, over a 2-month period in 2006 to 2007. The main outcome variables were 14- and 30-day mortality. Adjusted analyses were performed by multivariate analysis and propensity score-based matching. Eight hundred one episodes were included. Inadequate empirical therapy was administered in 199 (24.8%) episodes; mortality at days 14 and 30 was 18.55% and 22.6%, respectively. After controlling for age, Charlson index, Pitt score, neutropenia, source, etiology, and presentation with severe sepsis or shock, inadequate empirical treatment was associated with increased mortality at days 14 and 30 (odds ratios [ORs], 2.12 and 1.56; 95% confidence intervals [95% CI], 1.34 to 3.34 and 1.01 to 2.40, respectively). The adjusted ORs after a propensity score-based matched analysis were 3.03 and 1.70 (95% CI, 1.60 to 5.74 and 0.98 to 2.98, respectively). In conclusion, inadequate empirical therapy is independently associated with increased mortality in patients with BSI. Programs to improve the quality of empirical therapy in patients with suspicion of BSI and optimization of definitive therapy should be implemented.

Diagnosing Patients Combining Principal Components Analysis and Case Based Reasoning

This paper addresses the application of a PCA analysis on categorical data prior to diagnose a patients data set using a Case-Based Reasoning (CBR) system. The particularity is that the standard PCA techniques are designed to deal with numerical attributes, but our medical data set contains many categorical data and alternative methods as RS-PCA are required. Thus, we propose to hybridize RS-PCA (Regular Simplex PCA) and a simple CBR. Results show how the hybrid system produces similar results when diagnosing a medical data set, that the ones obtained when using the original attributes. These results are quite promising since they allow to diagnose with less computation effort and memory storage

Elemental analysis of New Zealand Nephrite Jade (pounamu) for forensic purposes

Pounamu (NZ jade), or nephrite, is a protected mineral in its natural form following thetransfer of ownership back to Ngai Tahu under the Ngai Tahu (Pounamu Vesting) Act 1997.Any theft of nephrite is prosecutable under the Crimes Act 1961. Scientific evidence isessential in cases where origin is disputed. A robust method for discrimination of thismaterial through the use of elemental analysis and compositional data analysis is required.Initial studies have characterised the variability within a given nephrite source. This hasincluded investigation of both in situ outcrops and alluvial material. Methods for thediscrimination of two geographically close nephrite sources are being developed.Key Words: forensic, jade, nephrite, laser ablation, inductively coupled plasma massspectrometry, multivariate analysis, elemental analysis, compositional data analysis

Relationship of imatinib-free plasma levels and target genotype with efficacy and tolerability

Imatinib has revolutionised the treatment of chronic myeloid leukaemia (CML) and gastrointestinal stromal tumours (GIST). Using a nonlinear mixed effects population model, individual estimates of pharmacokinetic parameters were derived and used to estimate imatinib exposure (area under the curve, AUC) in 58 patients. Plasma-free concentration was deduced from a model incorporating plasma levels of alpha(1)-acid glycoprotein. Associations between AUC (or clearance) and response or incidence of side effects were explored by logistic regression analysis. Influence of KIT genotype was also assessed in GIST patients. Both total (in GIST) and free drug exposure (in CML and GIST) correlated with the occurrence and number of side effects (e.g. odds ratio 2.7+/-0.6 for a two-fold free AUC increase in GIST; P<0.001). Higher free AUC also predicted a higher probability of therapeutic response in GIST (odds ratio 2.6+/-1.1; P=0.026) when taking into account tumour KIT genotype (strongest association in patients harbouring exon 9 mutation or wild-type KIT, known to decrease tumour sensitivity towards imatinib). In CML, no straightforward concentration-response relationships were obtained. Our findings represent additional arguments to further evaluate the usefulness of individualizing imatinib prescription based on a therapeutic drug monitoring programme, possibly associated with target genotype profiling of patients.

Effects of KRAS, BRAF, NRAS, and PIK3CA mutations on the efficacy of cetuximab plus chemotherapy in chemotherapy-refractory metastatic colorectal cancer: a retrospective consortium analysis.

Background Following the discovery that mutant KRAS is associated with resistance to anti-epidermal growth factor receptor (EGFR) antibodies, the tumours of patients with metastatic colorectal cancer are now profiled for seven KRAS mutations before receiving cetuximab or panitumumab. However, most patients with KRAS wild-type tumours still do not respond. We studied the effect of other downstream mutations on the efficacy of cetuximab in, to our knowledge, the largest cohort to date of patients with chemotherapy-refractory metastatic colorectal cancer treated with cetuximab plus chemotherapy in the pre-KRAS selection era. Methods 1022 tumour DNA samples (73 from fresh-frozen and 949 from formalin-fixed, paraffin-embedded tissue) from patients treated with cetuximab between 2001 and 2008 were gathered from 11 centres in seven European countries. 773 primary tumour samples had sufficient quality DNA and were included in mutation frequency analyses; mass spectrometry genotyping of tumour samples for KRAS, BRAF, NRAS, and PIK3CA was done centrally. We analysed objective response, progression-free survival (PFS), and overall survival in molecularly defined subgroups of the 649 chemotherapy-refractory patients treated with cetuximab plus chemotherapy. Findings 40.0% (299/747) of the tumours harboured a KRAS mutation, 14.5% (108/743) harboured a PIK3CA mutation (of which 68.5% [74/108] were located in exon 9 and 20.4% [22/108] in exon 20), 4.7% (36/761) harboured a BRAF mutation, and 2.6% (17/644) harboured an NRAS mutation. KRAS mutants did not derive benefit compared with wild types, with a response rate of 6.7% (17/253) versus 35.8% (126/352; odds ratio [OR] 0.13, 95% CI 0.07-0.22; p<0.0001), a median PFS of 12. weeks versus 24 weeks (hazard ratio [HR] 1 98, 1.66-2.36; p<0.0001), and a median overall survival of 32 weeks versus 50 weeks (1.75, 1.47-2.09; p<0.0001). In KRAS wild types, carriers of BRAF and NRAS mutations had a significantly lower response rate than did BRAF and NRAS wild types, with a response rate of 8.3% (2/24) in carriers of BRAF mutations versus 38.0% in BRAF wild types (124/326; OR 0.15, 95% CI 0.02-0.51; p=0.0012); and 7.7% (1/13) in carriers of NRAS mutations versus 38.1% in NRAS wild types (110/289; OR 0.14, 0.007-0.70; p=0.013). PIK3CA exon 9 mutations had no effect, whereas exon 20 mutations were associated with a worse outcome compared with wild types, with a response rate of 0.0% (0/9) versus 36.8% (121/329; OR 0.00,0.00-0.89; p=0.029), a median PFS of 11.5 weeks versus 24 weeks (HR 2.52, 1.33-4.78; p=0.013), and a median overall survival of 34 weeks versus 51 weeks (3.29, 1.60-6.74; p=0.0057). Multivariate analysis and conditional inference trees confirmed that, if KRAS is not mutated, assessing BRAF, NRAS, and PIK3CA exon 20 mutations (in that order) gives additional information about outcome. Objective response rates in our series were 24.4% in the unselected population, 36.3% in the KRAS wild-type selected population, and 41.2% in the KRAS, BRAF, NRAS, and PIK3CA exon 20 wild-type population. Interpretation While confirming the negative effect of KRAS mutations on outcome after cetuximab, we show that BRAF, NRAS, and PIK3CA,exon 20 mutations are significantly associated with a low response rate. Objective response rates could be improved by additional genotyping of BRAF, NRAS, and PIK3CA exon 20 mutations in a KRAS wild-type population.

Some last thoughts on compositional data analysis

One of the disadvantages of old age is that there is more past than future: this,however, may be turned into an advantage if the wealth of experience and, hopefully,wisdom gained in the past can be reflected upon and throw some light on possiblefuture trends. To an extent, then, this talk is necessarily personal, certainly nostalgic,but also self critical and inquisitive about our understanding of the discipline ofstatistics. A number of almost philosophical themes will run through the talk: searchfor appropriate modelling in relation to the real problem envisaged, emphasis onsensible balances between simplicity and complexity, the relative roles of theory andpractice, the nature of communication of inferential ideas to the statistical layman, theinter-related roles of teaching, consultation and research. A list of keywords might be:identification of sample space and its mathematical structure, choices betweentransform and stay, the role of parametric modelling, the role of a sample spacemetric, the underused hypothesis lattice, the nature of compositional change,particularly in relation to the modelling of processes. While the main theme will berelevance to compositional data analysis we shall point to substantial implications forgeneral multivariate analysis arising from experience of the development ofcompositional data analysis…

Achievement of at least very good partial response is a simple and robust prognostic factor in patients with multiple myeloma treated with high-dose therapy: long-term analysis of the IFM 99-02 and 99-04 Trials.

PURPOSE: The prognostic impact of complete response (CR) achievement in multiple myeloma (MM) has been shown mostly in the context of autologous stem-cell transplantation. Other levels of response have been defined because, even with high-dose therapy, CR is a relatively rare event. The purpose of this study was to analyze the prognostic impact of very good partial response (VGPR) in patients treated with high-dose therapy. PATIENTS AND METHODS: All patients were included in the Intergroupe Francophone du Myelome 99-02 and 99-04 trials and treated with vincristine, doxorubicin, and dexamethasone (VAD) induction therapy followed by double autologous stem-cell transplantation (ASCT). Best post-ASCT response assessment was available for 802 patients. RESULTS: With a median follow-up of 67 months, median event-free survival (EFS) and 5-year EFS were 42 months and 34%, respectively, for 405 patients who achieved at least VGPR after ASCT versus 32 months and 26% in 288 patients who achieved only partial remission (P = .005). Five-year overall survival (OS) was significantly superior in patients achieving at least VGPR (74% v 61% P = .0017). In multivariate analysis, achievement of less than VGPR was an independent factor predicting shorter EFS and OS. Response to VAD had no impact on EFS and OS. The impact of VGPR achievement on EFS and OS was significant in patients with International Staging System stages 2 to 3 and for patients with poor-risk cytogenetics t(4;14) or del(17p). CONCLUSION: In the context of ASCT, achievement of at least VGPR is a simple prognostic factor that has importance in intermediate and high-risk MM and can be informative in more patients than CR.

Injection drug use before and after liver transplantation: a retrospective multicenter analysis on incidence and outcome.

De Gottardi A, Hilleret M-N, Gelez P, La Mura V, Guillaud O, Majno P, Hadengue A, Morel P, Zarski J-P, Fontana M, Moradpour D, Mentha G, Boillot O, Leroy V, Giostra E, Dumortier J. Injection drug use before and after liver transplantation: a retrospective multicenter analysis on incidence and outcome. Clin Transplant 2009 DOI: 10.1111/j.1399-0012.2009.01121.x.Background and aims: Injecting drug use (IDU) before and after liver transplantation (LT) is poorly described. The aim of this study was to quantify relapse and survival in this population and to describe the causes of mortality after LT. Methods: Past injection drug users were identified from the LT listing protocols from four centers in Switzerland and France. Data on survival and relapse were collected and used for uni- and multivariate analysis. Results: Between 1988 and 2006, we identified 59 patients with a past history of IDU. The mean age at transplantation was 42.4 yr and the majority of patients were men (84.7%). The indication for LT was for the vast majority viral cirrhosis accounting for 91.5% of cases, while alcoholic cirrhosis was 5.1%. There were 16.9% of patients who had a substitution therapy before and 6.8% who continued after LT. Two patients (3.4%) relapsed into IDU after LT and died at 18 and 41 months. The mean follow-up was 51 months. Overall survival was 84%, 66%, and 61% at 1, 5, and 10 yr after transplantation. Conclusions: Documented IDU was rare in liver transplanted patients. Past IDU was not associated with poorer survival after LT, and relapse after LT occurred in 3.4%.