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Regression Methods (regression + methods)
Kinds of Regression Methods Selected AbstractsModern Regression Methods, Second Edition by Thomas P. RyanINTERNATIONAL STATISTICAL REVIEW, Issue 2 2009Norman R. Draper No abstract is available for this article. [source] Cox Regression Methods for Two-Stage Randomization DesignsBIOMETRICS, Issue 2 2007Yuliya Lokhnygina Summary Two-stage randomization designs (TSRD) are becoming increasingly common in oncology and AIDS clinical trials as they make more efficient use of study participants to examine therapeutic regimens. In these designs patients are initially randomized to an induction treatment, followed by randomization to a maintenance treatment conditional on their induction response and consent to further study treatment. Broader acceptance of TSRDs in drug development may hinge on the ability to make appropriate intent-to-treat type inference within this design framework as to whether an experimental induction regimen is better than a standard induction regimen when maintenance treatment is fixed. Recently Lunceford, Davidian, and Tsiatis (2002, Biometrics58, 48,57) introduced an inverse probability weighting based analytical framework for estimating survival distributions and mean restricted survival times, as well as for comparing treatment policies at landmarks in the TSRD setting. In practice Cox regression is widely used and in this article we extend the analytical framework of Lunceford et al. (2002) to derive a consistent estimator for the log hazard in the Cox model and a robust score test to compare treatment policies. Large sample properties of these methods are derived, illustrated via a simulation study, and applied to a TSRD clinical trial. [source] Phosphatidylethanol and Alcohol Consumption in Reproductive Age WomenALCOHOLISM, Issue 3 2010Scott H. Stewart Background:, Fetal alcohol disorders are preventable, but self-reported alcohol consumption can be misleading and impede effective treatment. Biomarkers represent an alternative method for assessing alcohol use, and this study evaluated the relationship between blood phosphatidylethanol (PEth) and alcohol use in a sample of reproductive age women. Methods:, Alcohol use was estimated by validated self-report methods in 80 nonpregnant women ages 18 to 35. PEth was measured by a contracted laboratory using a liquid chromatography-tandem mass spectrometry assay. Regression methods appropriate for the distribution of PEth were used to define its relationship to alcohol consumption during the prior 2 weeks and explore the effects of drinking patterns on this association. Receiver operating characteristic analysis was used to estimate the sensitivity of PEth for various drinking levels at 95% specific cutoffs. Results:, PEth had a positive linear association with grams of alcohol consumed (p < 0.001), and was detectable in 93% of subjects consuming an average of 2 or more drinks per day. The relationship between total alcohol consumption and PEth may be stronger in women with recent heavy drinking days. The relationship between drinking and PEth varied considerably between individuals, and sensitivity for a certain amount of drinking was low at a highly specific cutoff concentration. Conclusions:, PEth is a highly sensitive indicator of moderate and heavy alcohol consumption in reproductive age women and may complement the use of self-report alcohol screens when additional objective markers of alcohol use are desirable. However, choosing a highly valid cutoff concentration for PEth to differentiate various levels of alcohol consumption may not be feasible. [source] Regression methods for correcting salary inequities between groups of academic employeesNEW DIRECTIONS FOR INSTITUTIONAL RESEARCH, Issue 115 2002Ronald L. Oaxaca This chapter explores some of the ways in which an institution can make salary adjustments to remove salary inequities for individuals. A new approach is developed for correcting salary inequities. [source] Quantitative trait loci for performance traits in a broiler × layer crossANIMAL GENETICS, Issue 2 2009M. Ambo Summary An F2 resource population, derived from a broiler × layer cross, was used to map quantitative trait loci (QTL) for body weights at days 1, 35 and 41, weight gain, feed intake, feed efficiency from 35 to 41 days and intestinal length. Up to 577 F2 chickens were genotyped with 103 genetic markers covering 21 linkage groups. A preliminary QTL mapping report using this same population focused exclusively on GGA1. Regression methods were applied to line-cross and half-sib models for QTL interval mapping. Under the line-cross model, eight QTL were detected for body weight at 35 days (GGA2, 3 and 4), body weight at 41 days (GGA2, 3, 4 and 10) and intestine length (GGA4). Under the half-sib model, using sire as common parent, five QTL were detected for body weight at day 1 (GGA3 and 18), body weight at 35 days (GGA2 and 3) and body weight at 41 days (GGA3). When dam was used as common parent, seven QTL were mapped for body weight at day 1 (GGA2), body weight at day 35 (GGA2, 3 and 4) and body weight at day 41 (GGA2, 3 and 4). Growth differences in chicken lines appear to be controlled by a chronological change in a limited number of chromosomal regions. [source] Lower suicide risk with long-term lithium treatment in major affective illness: a meta-analysisACTA PSYCHIATRICA SCANDINAVICA, Issue 3 2001Leonardo Tondo Objective:,To compare suicide rates with vs. without long-term lithium treatment in major affective disorders. Method:,Broad searching yielded 22 studies providing suicide rates during lithium maintenance; 13 also provide rates without such treatment. Study quality was scored, between-study variance tested, and suicide rates on vs. off lithium examined by meta-analyses using random-effects regression methods to model risk ratios. Results:,Among 5647 patients (33,473 patient-years of risk) in 22 studies, suicide was 82% less frequent during lithium-treatment (0.159 vs. 0.875 deaths/100 patient-years). The computed risk-ratio in studies with rates on/off lithium was 8.85 (95% CI, 4.12,19.1; P<0.0001). Higher rates off-lithium were not accounted for by treatment-discontinuation. Conclusion:,Suicide risk was consistently lower during long-term treatment of major affective illnesses with lithium in all studies in the meta-analysis, including the few involving treatment-randomization. [source] Obesity and lifestyle risk factors for gastroesophageal reflux disease, Barrett esophagus and esophageal adenocarcinomaDISEASES OF THE ESOPHAGUS, Issue 5 2006P. J. Veugelers SUMMARY., The aim of this study was to examine the association of obesity with esophageal adenocarcinoma, and with the precursor lesions Barrett esophagus and gastroesophageal reflux disease (GERD). This case-control study included cases with GERD (n = 142), Barrett esophagus (n = 130), and esophageal adenocarcinoma (n = 57). Controls comprised 102 asymptomatic individuals. Using logistic regression methods, we compared obesity rates between cases and controls adjusting for differences in age, gender, and lifestyle risk factors. Relative to normal weight, obese individuals were at increased risk for esophageal adenocarcinoma (Odds Ratio [OR] 4.67, 95% Confidence Interval [CI] 1.27,17.9). Diets high in vitamin C were associated with a lower risk for GERD (OR 0.40, 95% CI 0.19,0.87), Barrett esophagus (OR 0.44, 95% CI 0.20,0.98), and esophageal adenocarcinoma (OR 0.21, 95% CI 0.06,0.77). For the more established risk factors, we confirmed that smoking was a significant risk factor for esophageal adenocarcinoma, and that increased liquor consumption was associated with GERD and Barrett esophagus. In light of the current obesity epidemic, esophageal adenocarcinoma incidence rates are expected to continue to increase. Successful promotion of healthy body weight and diets high in vitamin C may substantially reduce the incidence of this disease. [source] Genetic influences on reading difficulties in boys and girls: the Colorado twin studyDYSLEXIA, Issue 1 2006Jesse L. Hawke Abstract To test the hypothesis that the genetic etiology for reading disability may differ in males and females, data from identical and fraternal twin pairs were analysed using both concordance and multiple regression methods. The sample included 264 identical (129 male, 135 female) and 214 same-sex fraternal (121 male, 93 female) twin pairs in which at least one member of each pair had reading difficulties. The difference between the identical and fraternal twin pair concordance rates was slightly larger for females than for males, suggesting a possible sex difference in etiology; however, a loglinear analysis of the three-way interaction of sex, zygosity, and concordance was not significant (p,0.17). The estimate of group heritability (hg2), a standardized measure of the extent to which reading difficulties are due to genetic influences, was somewhat greater for females than males (0.65 vs 0.54), but this difference was also not significant (p,0.35). Gender differences in hg2 were larger for younger children (less than 11.5 years of age) than for older children. However, the three-way interaction of sex, zygosity, and age was not significant when age was treated either categorically (p,0.86) or continuously (p,0.71). Thus, results of this study provide little or no evidence for a differential genetic etiology of reading difficulties in males and females. Copyright © 2005 John Wiley & Sons, Ltd. [source] Are spatial regression methods a panacea or a Pandora's box?ECOGRAPHY, Issue 6 2007A reply to Beale et al. (2007) First page of article [source] Behavior of interacting species in vacancy affinity capillary electrophoresis described by mass balance equationELECTROPHORESIS, Issue 16 2008Ying Sun Abstract Vacancy ACE (VACE) is one of the ACE methods, and has been used to study binding interactions between different biomolecules. Thermodynamic binding constants can be estimated with nonlinear regression methods. With a highly efficient computer simulation program (SimDCCE), it is possible to demonstrate the detailed behaviors of each species during the interaction process under different conditions. In this work, thirteen scenarios in four different combinations of migration orders of the free protein, free drug, and complex formed are studied. The detailed interaction process between protein and ligand is discussed and illustrated based on the mass balance equation, also called mass transfer equation. By properly setting the parameters in the simulation model, the influence of different factors during the interaction process can be well understood. [source] Evaluation of statistical methods for left-censored environmental data with nonuniform detection limitsENVIRONMENTAL TOXICOLOGY & CHEMISTRY, Issue 9 2006Parikhit Sinha Abstract Monte Carlo simulations were used to evaluate statistical methods for estimating 95% upper confidence limits of mean constituent concentrations for left-censored data with nonuniform detection limits. Two primary scenarios were evaluated: data sets with 15 to 50% nondetected samples and data sets with 51 to 80% nondetected samples. Sample size and the percentage of nondetected samples were allowed to vary randomly to generate a variety of left-censored data sets. All statistical methods were evaluated for efficacy by comparing the 95% upper confidence limits for the left-censored data with the 95% upper confidence limits for the noncensored data and by determining percent coverage of the true mean (,). For data sets with 15 to 50% nondetected samples, the trimmed mean, Winsorization, Aitchison's, and log-probit regression methods were evaluated. The log-probit regression was the only method that yielded sufficient coverage (99,100%) of ,, as well as a high correlation coefficient (r2 = 0.99) and small average percent residuals (, 0.1%) between upper confidence limits for censored versus noncensored data sets. For data sets with 51 to 80% nondetected samples, a bounding method was effective (r2 = 0.96,0.99, average residual = ,5% to ,7%, 95-98% coverage of ,), except when applied to distributions with low coefficients of variation (standard deviation/, < 0.5). Thus, the following recommendations are supported by this research: data sets with 15 to 50% nondetected samples,log-probit regression method and use of Chebyshev theorem to estimate 95% upper confidence limits; data sets with 51 to 80% nondetected samples, bounding method and use of Chebyshev theorem to estimate 95% upper confidence limits. [source] EVOLUTIONARY POTENTIAL OF A LARGE MARINE VERTEBRATE: QUANTITATIVE GENETIC PARAMETERS IN A WILD POPULATIONEVOLUTION, Issue 4 2009Joseph D. DiBattista Estimating quantitative genetic parameters ideally takes place in natural populations, but relatively few studies have overcome the inherent logistical difficulties. For this reason, no estimates currently exist for the genetic basis of life-history traits in natural populations of large marine vertebrates. And yet such estimates are likely to be important given the exposure of this taxon to changing selection pressures, and the relevance of life-history traits to population productivity. We report such estimates from a long-term (1995,2007) study of lemon sharks (Negaprion brevirostris) conducted at Bimini, Bahamas. We obtained these estimates by genetically reconstructing a population pedigree (117 dams, 487 sires, and 1351 offspring) and then using an "animal model" approach to estimate quantitative genetic parameters. We find significant additive genetic (co)variance, and hence moderate heritability, for juvenile length and mass. We also find substantial maternal effects for these traits at age-0, but not age-1, confirming that genotype,phenotype interactions between mother and offspring are strongest at birth; although these effects could not be parsed into their genetic and nongenetic components. Our results suggest that human-imposed selection pressures (e.g., size-selective harvesting) might impose noteworthy evolutionary change even in large marine vertebrates. We therefore use our findings to explain how maternal effects may sometimes promote maladaptive juvenile traits, and how lemon sharks at different nursery sites may show "constrained local adaptation." We also show how single-generation pedigrees, and even simple marker-based regression methods, can provide accurate estimates of quantitative genetic parameters in at least some natural systems. [source] Population size, weight distribution and food in a persistent population of the rare medicinal leech, Hirudo medicinalisFRESHWATER BIOLOGY, Issue 8 2008J. M. ELLIOTT Summary 1. It is important for species recovery and conservation management projects to know the minimum viable population size for rare and endangered species, such as the medicinal leech, Hirudo medicinalis. Therefore, using a catch-removal method, this study estimated every two years (1986, 1988, 1990, 1992) the total number of medicinal leeches in a tarn in the English Lake District, and the number of mature adults in the population. 2. Four samples were taken each year in June and July, when water temperatures exceeded 20 °C. Population size was estimated both by maximum likelihood and regression methods. All leeches were weighed alive and size groups were separated by polymodal frequency analysis. A small sample of the blood meal in each leech gut was taken before the leeches were returned to the tarn, and was used to estimate the proportion of mammalian and non-mammalian blood in the meals. 3. Both methods of estimation produced similar values, increasing confidence in the population estimates. Values for the total population in June and July varied among years from 248 to 288, the maximum value being only 16% higher than the minimum. Values for the number of mature leeches varied from 48 to 58 (19,20% of the total population), and this was an estimate of the effective population size. 4. There were four size groups. The largest mature leeches (live weight >5 g) in group IV formed only 1% of the population, and the smallest (0.02,0.5 g) in group I 14,17%. Most leeches were in two overlapping groups of immature (64,67% of population) and mature (18%) leeches with size ranges of 0.4,3.4 g and 2.5,5 g respectively. The percentage of leeches in each size group was very consistent among years. Blood meals were found in 38,44% of the leeches in group I, 45,50% in group II, 70,75% in group III, and 100% in group IV, but mammalian blood was present only in larger mature leeches (>3.5 g). 5. Medicinal leeches were first detected in the tarn in 1980 and are still present in 2007, so the population has persisted for at least 27 years. Compared with minimum viable population sizes for other species, including many endangered species, values for this medicinal leech population are extremely low, but may be typical of some rare freshwater invertebrates in isolated habitats. [source] Genetic analysis of phenotypes derived from longitudinal data: Presentation Group 1 of Genetic Analysis Workshop 13GENETIC EPIDEMIOLOGY, Issue S1 2003Konstantin Strauch Abstract The participants of Presentation Group 1 used the GAW13 data to derive new phenotypes, which were then analyzed for linkage and, in one case, for association to the genetic markers. Since the trait measurements ranged over longer time periods, the participants looked at the time dependence of particular traits in addition to the trait itself. The phenotypes analyzed with the Framingham data can be roughly divided into 1) body weight-related traits, which also include a type 2 diabetes progression trait, and 2) traits related to systolic blood pressure. Both trait classes are associated with metabolic syndrome. For traits related to body weight, linkage was consistently identified by at least two participating groups to genetic regions on chromosomes 4, 8, 11, and 18. For systolic blood pressure, or its derivatives, at least two groups obtained linkage for regions on chromosomes 4, 6, 8, 11, 14, 16, and 19. Five of the 13 participating groups focused on the simulated data. Due to the rather sparse grid of microsatellite markers, an association analysis for several traits was not successful. Linkage analysis of hypertension and body mass index using LODs and heterogeneity LODs (HLODs) had low power. For the glucose phenotype, a combination of random coefficient regression models and variance component linkage analysis turned out to be strikingly powerful in the identification of a trait locus simulated on chromosome 5. Haseman-Elston regression methods, applied to the same phenotype, had low power, but the above-mentioned chromosome 5 locus was not included in this analysis. Genet Epidemiol 25 (Suppl. 1):S5,S17, 2003. © 2003 Wiley-Liss, Inc. [source] Evaluation of coalbed methane reservoirs from geophysical log data using an improved fuzzy comprehensive decision method and a homologous neural networkGEOPHYSICAL PROSPECTING, Issue 5 2002J. Hou The evaluation of coalbed methane reservoirs using log data is an important approach in the exploration and development of coalbed methane reservoirs. Most commonly, regression techniques, fuzzy recognition and neural networks have been used to evaluate coalbed methane reservoirs. It is known that a coalbed is an unusual reservoir. There are many difficulties in using regression methods and empirical qualitative recognition to evaluate a coalbed, but fuzzy recognition, such as the fuzzy comprehensive decision method, and neural networks, such as the back-propagation (BP) network, are widely used. However, there are no effective methods for computing weights for the fuzzy comprehensive decision method, and the BP algorithm is a local optimization algorithm, easily trapped in local minima, which significantly affect the results. In this paper, the recognition method for coal formations is developed; the improved fuzzy comprehensive decision method, which uses an optimization approach for computing weighted coefficients, is developed for the qualitative recognition of coalbed methane reservoirs. The homologous neural network, using a homologous learning algorithm, which is a global search optimization, is presented for the quantitative analysis of parameters for coalbed methane reservoirs. The applied procedures for these methods and some problems related to their application are also discussed. Verification of the above methods is made using log data from the coalbed methane testing area in North China. The effectiveness of the methods is demonstrated by the analysis of results for real log data. [source] Welfare Reform and Health Insurance of ImmigrantsHEALTH SERVICES RESEARCH, Issue 3 2005Neeraj Kaushal Objective. To investigate the effect of the Personal Responsibility and Work Opportunity Reconciliation Act (PRWORA) on the health insurance coverage of foreign- and U.S.-born families headed by low-educated women. Data Source. Secondary data from the March series of the Current Population Surveys for 1994,2001. Study Design. Multivariate regression methods and a pre- and post-test with comparison group research design (difference-in-differences) are used to estimate the effect of welfare reform on the health insurance coverage of low-educated, foreign- and U.S.-born unmarried women and their children. Heterogenous responses by states to create substitute Temporary Aid to Needy Families or Medicaid programs for newly arrived immigrants are used to investigate whether the estimated effect of PRWORA on newly arrived immigrants is related to the actual provisions of the law, or the result of fears engendered by the law. Principal Findings. PRWORA increased the proportion of uninsured among low-educated, foreign-born, unmarried women by 9.9,10.7 percentage points. In contrast, the effect of PRWORA on the health insurance coverage of similar U.S.-born women is negligible. PRWORA also increased the proportion of uninsured among foreign-born children living with low-educated, single mothers by 13.5 percentage points. Again, the policy had little effect on the health insurance coverage of the children of U.S.-born, low-educated single mothers. There is some evidence that the fear and uncertainty engendered by the law had an effect on immigrant health insurance coverage. Conclusions. This research demonstrates that PRWORA adversely affected the health insurance of low-educated, unmarried, immigrant women and their children. In the case of unmarried women, it may be partly because the jobs that they obtained in response to PRWORA were less likely to provide health insurance. The research also suggests that PRWORA may have engendered fear among immigrants and dampened their enrollment in safety net programs. [source] Nonlinear multiple regression methods: a survey and extensionsINTELLIGENT SYSTEMS IN ACCOUNTING, FINANCE & MANAGEMENT, Issue 1 2010Kenneth O. Cogger Abstract This paper reviews some nonlinear statistical procedures useful in function approximation, classification, regression and time-series analysis. Primary emphasis is on piecewise linear models such as multivariate adaptive regression splines, adaptive logic networks, hinging hyperplanes and their conceptual differences. Potential and actual applications of these methods are cited. Software for implementation is discussed, and practical suggestions are given for improvement. Examples show the relative capabilities of the various methods, including their ability for universal approximation. Copyright © 2010 John Wiley & Sons, Ltd. [source] Piece Rates, Fixed Wages, and Incentive Effects: Statistical Evidence from Payroll RecordsINTERNATIONAL ECONOMIC REVIEW, Issue 1 2000Harry J. Paarsch We develop and estimate an agency model of worker behavior under piece rates and fixed wages. The model implies optimal decision rules for the firm's choice of a compensation system as a function of working conditions. Our model also implies an upper and lower bound to the incentive effect (the productivity gain realized by paying workers piece rates rather than fixed wages) that can be estimated using regression methods. Using daily productivity data collected from the payroll records of a British Columbia tree-planting firm, we estimate these bounds to be an 8.8 and a 60.4 percent increase in productivity. Structural estimation, which accounts for the firm's optimal choice of a compensation system, suggests that incentives caused a 22.6 percent increase in productivity. However, only part of this increase represents valuable output because workers respond to incentives, in part, by reducing quality. [source] Isothiocyanates, glutathione S -transferase M1 and T1 polymorphisms and gastric cancer risk: A prospective study of men in Shanghai, ChinaINTERNATIONAL JOURNAL OF CANCER, Issue 11 2009Kristin A. Moy Abstract Isothiocyanates (ITC) in cruciferous vegetables may be chemopreventive against gastric cancer development. Glutathione S -transferases (GSTs) may modify the chemopreventive effect of ITC. The relationship between urinary total ITC and risk of gastric cancer was prospectively examined. Between 1986 and 1989, 18,244 middle-aged men in Shanghai, China were enrolled in a prospective study of diet and cancer and donated baseline urine and blood samples. Urinary ITC was quantified for 307 incident cases of gastric cancer that occurred during the first 16 years of follow-up, and 911 matched control subjects. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using logistic regression methods. Seropositivity for antibodies to Helicobacter pylori and homozygous deletions of GSTM1 and GSTT1 were determined. Compared to the first tertile, ORs (95% CIs) of gastric cancer for the second and third tertiles of urinary total ITC were 0.83 (0.61,1.15) and 0.66 (0.47,0.94) (ptrend = 0.02). A stronger protective effect of ITC against gastric cancer development was seen among men with homozygous deletion of GSTM1 (third tertile versus first tertile, OR = 0.50, 95% CI = 0.27,0.93) or GSTT1 (third tertile vs. first tertile, OR = 0.47, 95% CI = 0.25,0.88), and particularly with deletions of both GSTM1 and GSTT1 (second and third tertiles vs. first tertile, OR = 0.44, 95% CI = 0.21,0.93). In this cohort of Chinese men at high risk for gastric cancer, isothiocyanates may protect against the development of gastric cancer. The protection may be stronger for individuals genetically deficient in enzymes that metabolize these chemopreventive compounds. © 2009 UICC [source] Roman Period fetal skeletons from the East Cemetery (Kellis 2) of Kellis, EgyptINTERNATIONAL JOURNAL OF OSTEOARCHAEOLOGY, Issue 5 2005M. W. Tocheri Abstract Much can be learned about the religious ideology and mortuary patterns as well as the demographic and health profiles of a population from archaeological human fetal skeletons. Fetal skeletons are rare, however, largely due to poor preservation and recovery, misidentification, or non-inclusion in general burial populations. We present an analysis of 82 fetal/perinatal skeletons recovered from Kellis 2, a Roman Period cemetery dated to the third and fourth centuries AD, located in the Dakhleh Oasis, Egypt. Most of the fetal remains were individually wrapped in linen and all were buried among the general cemetery population in a supine, east,west orientation with the head facing to the west. Gestational age estimates are calculated from diaphysis lengths using published regression and Bayesian methods. The overall similarity between the fetal age distributions calculated from the regression and Bayesian methods suggests that the correlation between diaphysis length and gestational age is typically strong enough to avoid the ,regression' problem of having the age structure of reference samples adversely affecting the age distribution of target samples. The inherent bias of the regression methods, however, is primarily reflected in the gestational age categories between 36 and 42 weeks corresponding with the expected increase in growth variation during the late third trimester. The results suggest that the fetal age distribution at Kellis 2 does not differ from the natural expected mortality distribution. Therefore, practices such as infanticide can be ruled out as having a significant effect on the observed mortality distribution. Moreover, the Kellis 2 sample is well represented in each gestational age category, suggesting that all premature stillbirths and neonatal deaths received similar burial rites. The age distribution of the Kellis 2 fetal remains suggests that emerging Christian concepts, such as the ,soul' and the ,afterlife', were being applied to everyone including fetuses of all gestational ages. Copyright © 2005 John Wiley & Sons, Ltd. [source] Towards a more general species,area relationship: diversity on all islands, great and smallJOURNAL OF BIOGEOGRAPHY, Issue 4 2001Lomolino Aim To demonstrate a new and more general model of the species,area relationship that builds on traditional models, but includes the provision that richness may vary independently of island area on relatively small islands (the small island effect). Location We analysed species,area patterns for a broad diversity of insular biotas from aquatic and terrestrial archipelagoes. Methods We used breakpoint or piecewise regression methods by adding an additional term (the breakpoint transformation) to traditional species,area models. The resultant, more general, species,area model has three readily interpretable, biologically relevant parameters: (1) the upper limit of the small island effect (SIE), (2) an estimate of richness for relatively small islands and (3) the slope of the species,area relationship (in semi-log or log,log space) for relatively large islands. Results The SIE, albeit of varying magnitude depending on the biotas in question, appeared to be a relatively common feature of the data sets we studied. The upper limit of the SIE tended to be highest for species groups with relatively high resource requirements and low dispersal abilities, and for biotas of more isolated archipelagoes. Main conclusions The breakpoint species,area model can be used to test for the significance, and to explore patterns of variation in small island effects, and to estimate slopes of the species,area (semi-log or log,log) relationship after adjusting for SIE. Moreover, the breakpoint species,area model can be expanded to investigate three fundamentally different realms of the species,area relationship: (1) small islands where species richness varies independent of area, but with idiosyncratic differences among islands and with catastrophic events such as hurricanes, (2) islands beyond the upper limit of SIE where richness varies in a more deterministic and predictable manner with island area and associated, ecological factors and (3) islands large enough to provide the internal geographical isolation (large rivers, mountains and other barriers within islands) necessary for in situ speciation. [source] A Haplotype-Based Analysis of the LRP5 Gene in Relation to Osteoporosis Phenotypes in Spanish Postmenopausal Women,JOURNAL OF BONE AND MINERAL RESEARCH, Issue 12 2008Lídia Agueda Abstract LRP5 encodes the low-density lipoprotein receptor-related protein 5, a transmembrane protein involved in Wnt signaling. LRP5 is an important regulator of osteoblast growth and differentiation, affecting bone mass in vertebrates. Whether common variations in LRP5 are associated with normal BMD variation or osteoporotic phenotypes is of great relevance. We used a haplotype-based approach to search for common disease-associated variants in LRP5 in a cohort of 964 Spanish postmenopausal women. Twenty-four SNPs were selected, covering the LRP5 region, including the missense changes p.V667M and p.A1330V. The SNPs were genotyped and evaluated for association with BMD at the lumbar spine (LS) or femoral neck (FN) and with osteoporotic fracture, at single SNP and haplotype levels, by regression methods. Association with LS BMD was found for SNP 1, rs312009, located in the 5,-flanking region (p = 0.011, recessive model). SNP 6, rs2508836, in intron 1, was also associated with BMD, both at LS (p = 0.025, additive model) and FN (p = 0.031, recessive model). Two polymorphisms were associated with fracture: SNP 11, rs729635, in intron 1, and SNP 15, rs643892, in intron 5 (p = 0.007 additive model and p = 0.019 recessive model, respectively). Haplotype analyses did not provide additional information, except for haplotype "GC" of the block located at the 3,end of the gene. This haplotype spans intron 22 and the 3, untranslated region and was associated with FN BMD (p = 0.029, one copy of the haplotype versus none). In silico analyses showed that SNP 1 (rs312009) lies in a putative RUNX2 binding site. Electro-mobility shift assays confirmed RUNX2 binding to this site. [source] The Time Series Properties of Financial Ratios: Lev RevisitedJOURNAL OF BUSINESS FINANCE & ACCOUNTING, Issue 5-6 2003Christos Ioannidis This paper re-evaluates the time series properties of financial ratios. It presents new empirical analysis which explicitly allows for the possibility that financial ratios can be characterized as non-linear mean-reverting processes. Financial ratios are widely employed as explanatory variables in accounting and finance research with applications ranging from the determinants of auditors' compensation to explaining firms' investment decisions. An implicit assumption in this empirical work is that the ratios are stationary so that the postulated models can be estimated by classical regression methods. However, recent empirical work on the time series properties of corporate financial ratios has reported that the level of the majority of ratios is described by non-stationary, I(1), integrated processes and that the ratio differences are parsimoniously described by random walks. We hypothesize that financial ratios may follow a random walk near their target level, but that the more distant a ratio is from target, the more likely the firm is to take remedial action to bring it back towards target. This behavior will result in a significant size distortion of the conventional stationarity tests and lead to frequent non-rejection of the null hypothesis of non-stationarity, a finding which undermines the use of these ratios as reliable conditioning variables for the explanation of firms' decisions. [source] An alignment-free methodology for modelling field-based 3D-structure activity relationships using inductive logic programmingJOURNAL OF CHEMOMETRICS, Issue 12 2007Bård Buttingsrud Abstract Traditional 3D-quantitative structure,activity relationship (QSAR)/structure,activity relationship (SAR) methodologies are sensitive to the quality of an alignment step which is required to make molecular structures comparable. Even though many methods have been proposed to solve this problem, they often result in a loss of model interpretability. The requirement of alignment is a restriction imposed by traditional regression methods due to their failure to represent relations between data objects directly. Inductive logic programming (ILP) is a class of machine-learning methods able to describe relational data directly. We propose a new methodology which is aimed at using the richness in molecular interaction fields (MIFs) without being restricted by any alignment procedure. A set of MIFs is computed and further compressed by finding their minima corresponding to the sites of strongest interaction between a molecule and the applied test probe. ILP uses these minima to build easily interpretable rules about activity expressed as pharmacophore rules in the powerful language of first-order logic. We use a set of previously published inhibitors of factor Xa of the benzamidine family to discuss the problems, requirements and advantages of the new methodology. Copyright © 2007 John Wiley & Sons, Ltd. [source] A comparative study of linear regression methods in noisy environmentsJOURNAL OF CHEMOMETRICS, Issue 12 2004Marco S. Reis Abstract With the development of measurement instrumentation methods and metrology, one is very often able to rigorously specify the uncertainty associated with each measured value (e.g. concentrations, spectra, process sensors). The use of this information, along with the corresponding raw measurements, should, in principle, lead to more sound ways of performing data analysis, since the quality of data can be explicitly taken into account. This should be true, in particular, when noise is heteroscedastic and of a large magnitude. In this paper we focus on alternative multivariate linear regression methods conceived to take into account data uncertainties. We critically investigate their prediction and parameter estimation capabilities and suggest some modifications of well-established approaches. All alternatives are tested under simulation scenarios that cover different noise and data structures. The results thus obtained provide guidelines on which methods to use and when. Interestingly enough, some of the methods that explicitly incorporate uncertainty information in their formulations tend to present not as good performances in the examples studied, whereas others that do not do so present an overall good performance. Copyright © 2005 John Wiley & Sons, Ltd. [source] Generalized orthogonal multiple co-inertia analysis(,PLS): new multiblock component and regression methodsJOURNAL OF CHEMOMETRICS, Issue 5 2003Myrtille Vivien Abstract The purpose of this paper is to develop new component-wise component and regression multiblock methods that overcome some of the difficulties traditionally associated with multiblocks, such as the step-by-step optimization and component orthogonalities. Generalized orthogonal multiple co-inertia analysis (GOMCIA) and generalized orthogonal multiple co-inertia analysis,partial least squares (GOMCIA,PLS) are proposed for modelling two sets of blocks measured on the same observations. We especially emphasize GOMCIA,PLS methods in which we consider one of the sets as predictive. All these methods are based on the step-by-step maximization of the same criterion under normalization constraints and produce orthogonal components or super-components. The solutions of the problem have to be computed with an iterative algorithm (which we prove to be convergent). We also give some interesting special cases and discuss the differences compared with a few other multiblock and/or multiway methods. Finally, short examples of real data are processed to show how GOMCIA,PLS can be used and its properties. Copyright © 2003 John Wiley & Sons, Ltd. [source] COVPROC method: strategy in modeling dynamic systemsJOURNAL OF CHEMOMETRICS, Issue 2 2003Satu-Pia Reinikainen Abstract A new procedure to select subsets in sequential dynamic systems is presented. Subsets of variables and samples to be included in a PLS model are considered. The approach is a combination of PLS analysis and standard regression methods. It is based on the H-principle of mathematical modeling, and therefore the aim is to balance improvement in fit and precision. One of the main aspects in the subset selection procedure is to keep the score space as large and as sensible as possible to gain a stable model. The procedure is described mathematically and demonstrated for a dynamic industrial case. The method is simple to apply and the motivation of the procedure is obvious for industrial applications. It can be used e.g. when modeling on-line systems. Copyright © 2003 John Wiley & Sons, Ltd. [source] Modelling near-infrared signals for on-line monitoring in cheese manufactureJOURNAL OF CHEMOMETRICS, Issue 2 2002B. J. A. Mertens Abstract This paper considers the analysis of a continuously monitored near-infrared reflectance signal at a single wavelength for the calibration of a process parameter in an application to food engineering for quality control. We describe how we may summarize the information in the observed signals by postulating an explicit statistical model on the signal. An exploratory data analysis may then be carried out on the profile summaries to evaluate whether and how the functional data provide information on the parameter which we would like to calibrate. From a conceptual point of view, such an approach is not dissimilar to principal component regression methods which use an intermediate decomposition through which information is summarised for calibration of a response. The paper demonstrates how the approach leads to important insights into the manner in which the functional data provide the required information on the desired outcome variable, in the context of the practical application in quality control which is discussed and by using a designed experiment. Calculations are implemented through the Gibbs sampler. Calibration of the prediction equation takes place through meta-analysis of the summarized profile data in order to take the uncertainty inherent in the summaries into account. Copyright © 2002 John Wiley & Sons, Ltd. [source] Precision of prediction in second-order calibration, with focus on bilinear regression methodsJOURNAL OF CHEMOMETRICS, Issue 1 2002Marie Linder Abstract We consider calibration of hyphenated instruments with particular focus on determination of the unknown concentrations of new specimens. A hyphenated instrument generates for each specimen a two-way array of data. These are assumed to depend on the concentrations through a bilinear regression model, where each constituent is characterized by a pair of profiles to be determined in the calibration. We discuss the problem of predicting the unknown concentrations in a new specimen, after calibration. We formulate three different predictor construction methods, a ,naive' method, a least squares method, and a refined version of the latter that takes account of the calibration uncertainty. We give formulae for the uncertainty of the predictors under white noise, when calibration can be seen as precise. We refine these formulae to allow for calibration uncertainty, in particular when calibration is carried out by the bilinear least squares (BLLS) method or the singular value decomposition (SVD) method proposed by Linder and Sundberg (Chemometrics Intell. Lab. Syst. 1998; 42: 159,178). By error propagation formulae and previous results on the precision of and we can obtain approximate standard errors for the predicted concentrations, according to each of the two estimation methods. The performance of the predictors and the precision formulae is illustrated on both real (fluorescence) and simulated data. Copyright © 2002 John Wiley & Sons, Ltd. [source] NEURAL NETWORK MODELING OF END-OVER-END THERMAL PROCESSING OF PARTICULATES IN VISCOUS FLUIDSJOURNAL OF FOOD PROCESS ENGINEERING, Issue 2010YANG MENG ABSTRACT Modeling of the heat transfer process in thermal processing is important for the process design and control. Artificial neural networks (ANNs) have been used in recent years in heat transfer modeling as a potential alternative to conventional dimensionless correlation approach and shown to be even better performers. In this study, ANN models were developed for apparent heat transfer coefficients associated with canned particulates in high viscous Newtonian and non-Newtonian fluids during end-over-end thermal processing in a pilot-scale rotary retort. A portion of experimental data obtained for the associated heat transfer coefficients were used for training while the rest were used for testing. The principal configuration parameters were the combination of learning rules and transfer functions, number of hidden layers, number of neurons in each hidden layer and number of learning runs. For the Newtonian fluids, the optimal conditions were two hidden layers, five neurons in each hidden layer, the delta learning rule, a sine transfer function and 40,000 learning runs, while for the non-Newtonian fluids, the optimal conditions were one hidden layer, six neurons in each hidden layer, the delta learning rule, a hyperbolic tangent transfer function and 50,000 learning runs. The prediction accuracies for the ANN models were much better compared with those from the dimensionless correlations. The trained network was found to predict responses with a mean relative error of 2.9,3.9% for the Newtonian fluids and 4.7,5.9% for the non-Newtonian fluids, which were 27,62% lower than those associated with the dimensionless correlations. Algebraic solutions were included, which could be used to predict the heat transfer coefficients without requiring an ANN. PRACTICAL APPLICATIONS The artificial neural network (ANN) model is a network of computational elements that was originally developed to mimic the function of the human brain. ANN models do not require the prior knowledge of the relationship between the input and output variables because they can discover the relationship through successive training. Moreover, ANN models can predict several output variables at the same time, which is difficult in general regression methods. ANN concepts have been successfully used in food processing for prediction, quality control and pattern recognition. ANN models have been used in recent years for heat transfer modeling as a potential alternative to conventional dimensionless correlation approach and shown to be even better performers. In this study, ANN models were successfully developed for the heat transfer parameters associated with canned particulate high viscous Newtonian and non-Newtonian fluids during an end-over-end rotation thermal processing. Optimized configuration parameters were obtained by choosing appropriate combinations of learning rule, transfer function, learning runs, hidden layers and number of neurons. The trained network was found to predict parameter responses with mean relative errors considerably lower than from dimensionless correlations. [source] | |||||||||||||||||||||||||||||||