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PubMed2000

Hemodynamic role of the circle of Willis in stenoses of internal carotid arteries. An analytical solution of a linear model.

A mathematical model of blood flow through the circle of Willis was developed, within a linear framework. Comprehensive analytical solutions, including a remarkably small number of parameters, were derived in the cases of obstructive lesions of extracranial carotid arteries. The influence of these lesions and the role of anterior and posterior communicating arteries on the blood pressure at the entry of the cerebral territories were quantified and analyzed emphasizing that the responses of the system of Willis to obstructive carotid lesions are extremely varied, depending on the communicating artery anatomy. Comparison with numerical results obtained by using a non-linear model showed no physiologically significant differences. Such a model might be an essential tool for an accurate assessment of the cerebral hemodynamics in carotid diseases.

Carotid Artery, Internal↗
PubMed1990

Log-linear models for cancer risk among migrants.

Epidemiological studies of migrants have played an important role in separating the environmental and genetic components of cancer aetiology. The statistical analyses of these studies have typically involved calculating age- and sex-adjusted rates by country of birth. We describe methods which permit the effect of duration of residence in the host country to be estimated after adjusting for other temporal effects such as age, and period or cohort. The methods, which are based on log-linear modelling, can also be applied in a case-control manner if appropriate denominator populations are unavailable. Examples are given in which the more traditional methods of analysis may have yielded misleading results.

Adolescent↗
PubMed2003

Setting priorities on waiting lists: point-count systems as linear models.

The Western Canada Waiting List Project (WCWL) is a federally funded initiative designed to develop tools for managing waiting lists. The principal tools developed by WCWL are point-count measures that assess the severity of patients' conditions and the extent of benefit expected from wait-listed services. Points are assigned according to the severity of patients' symptoms and clinical findings. Points on each factor are added and the total score is considered indicative of relative clinical urgency. Such point-count measures function as linear models from a statistical perspective. This paper describes the relevance of this functional relationship for the development and validation of priority criteria.

Activities of Daily Living↗
PubMed2001

fMRI activation in a visual-perception task: network of areas detected using the general linear model and independent components analysis.

The Motor-Free Visual Perception Test, revised (MVPT-R), provides a measure of visual perceptual processing. It involves different cognitive elements including visual discrimination, spatial relationships, and mental rotation. We adapted the MVPT-R to an event-related functional MRI (fMRI) environment to investigate the brain regions involved in the interrelation of these cognitive elements. Two complementary analysis methods were employed to characterize the fMRI data: (a) a general linear model SPM approach based upon a model of the time course and a hemodynamic response estimate and (b) independent component analysis (ICA), which does not constrain the specific shape of the time course per se, although we did require it to be at least transiently task-related. Additionally, we implemented ICA in a novel way to create a group average that was compared with the SPM group results. Both methods yielded similar, but not identical, results and detected a network of robustly activated visual, inferior parietal, and frontal eye-field areas as well as thalamus and cerebellum. SPM appeared to be the more sensitive method and has a well-developed theoretical approach to thresholding. The ICA method segregated functional elements into separate maps and identified additional regions with extended activation in response to presented events. The results demonstrate the utility of complementary analyses for fMRI data and suggest that the cerebellum may play a significant role in visual perceptual processing. Additionally, results illustrate functional connectivity between frontal eye fields and prefrontal and parietal regions.

Attention↗
PubMed1999

Solving large mixed linear models using preconditioned conjugate gradient iteration.

Continuous evaluation of dairy cattle with a random regression test-day model requires a fast solving method and algorithm. A new computing technique feasible in Jacobi and conjugate gradient based iterative methods using iteration on data is presented. In the new computing technique, the calculations in multiplication of a vector by a matrix were recorded to three steps instead of the commonly used two steps. The three-step method was implemented in a general mixed linear model program that used preconditioned conjugate gradient iteration. Performance of this program in comparison to other general solving programs was assessed via estimation of breeding values using univariate, multivariate, and random regression test-day models. Central processing unit time per iteration with the new three-step technique was, at best, one-third that needed with the old technique. Performance was best with the test-day model, which was the largest and most complex model used. The new program did well in comparison to other general software. Programs keeping the mixed model equations in random access memory required at least 20 and 435% more time to solve the univariate and multivariate animal models, respectively. Computations of the second best iteration on data took approximately three and five times longer for the animal and test-day models, respectively, than did the new program. Good performance was due to fast computing time per iteration and quick convergence to the final solutions. Use of preconditioned conjugate gradient based methods in solving large breeding value problems is supported by our findings.

Algorithms↗
PubMedDate not supplied

A linear model relating breath concentrations to environmental exposures: application to a chamber study of four volunteers exposed to volatile organic chemicals.

A linear model relating levels of volatile organic chemicals (VOCs) in exhaled breath to personal exposures at environmental (parts per billion) levels has been developed and evaluated in a chamber study of four human volunteers. The purpose of the model is to allow estimation of VOC concentrations in the body from measurements of exposure, or conversely to estimate previous exposure from a measurement of exhaled breath. The model differs from previous models in considering long-term inhalation at low or moderate concentrations rather than instantaneous intake (as in drug administration) or intermittent exposure at high concentrations (as in occupational situations). The model is based on a mass balance approach using one or more compartments to represent distribution of the chemical in the body. The main observable parameters in the model are the residence times tau 1 in the compartments, their "capacities" Ai, and the fraction f of the parent compound that is exhaled under equilibrium conditions. The basic equations for the one-, two-, three-, and n-compartment cases are derived. Solutions to these equations for the cases of a sudden constant high exposure, a sudden constant low exposure, and a linearly increasing exposure are provided. These solutions can be readily applied to more complex exposure scenarios. The chamber study suggests residence times on the order of a few minutes in the blood and 1-2 hr in the vessel-rich group of tissues. The design of the chamber study did not allow an estimate of the model parameters for fat; a subsequent chamber study has provided initial estimates of 50-100 hr. Field studies of personal exposures and breath concentrations of several hundred persons suggest values of f ranging from 0.1 for xylenes and ethylbenzene to about 0.9 for tetrachloroethylene.

Atmosphere Exposure Chambers↗
PubMed2006

Discrimination of errors from neuronal activity in functional MRI of the human spinal cord by means of general linear model analysis.

Functional MRI (fMRI) of the spinal cord has been demonstrated to provide reliable and sensitive maps of neuronal activity, particularly when combined across several experiments. Individual experiments reveal neuronal activity as well as errors. The dominant source of errors is hypothesized to be physiological motion, including cardiac and respiratory motion, flow of blood and cerebrospinal fluid (CSF), and motion of the spinal cord within the spinal canal. All of the hypothesized sources of error are therefore related to cardiac and respiratory motion, which can be recorded during an fMRI experiment. Analyses were carried out with a general linear model (GLM) with peripheral pulse and respiration recordings used as models of errors. The results demonstrate that the sensitivity of spinal fMRI is improved and errors are reduced when peripheral pulse traces are used in the GLM, but no improvement was detected with the inclusion of respiratory traces.

Humans↗
PubMed2003

Influence of clinical parameters on quality of life during chemotherapy in patients with advanced non-small cell lung cancer: application of a general linear model.

OBJECTIVE: The aim of this study was to determine the relative influence of physician-assessed clinical parameters, including non-hematological adverse events and performance status, on quality of life (QOL) during chemotherapy. METHODS: QOL questionnaires consisting of four domains (functional, physical, mental and psychosocial) were self-administered every week during chemotherapy by patients with advanced non-small cell lung cancer in two phase III clinical trials; 377 patients who completed the questionnaires at baseline and at least once during the first course of therapy were analyzed. A general linear model was applied, where the four domains and the clinical parameters (nausea/vomiting, anorexia, diarrhea, fever, peripheral neuropathy and performance status) were used as the response and explanatory variables, respectively. In this model, the multi-dimensional and longitudinal aspects of QOL data were taken into account. RESULTS: All four domains were significantly affected by the occurrence of nausea/vomiting, anorexia and diarrhea. No influence of peripheral neuropathy on the domains was detected. Performance status was significantly related to the domains (except the psychosocial domain). CONCLUSION: This study revealed, by examination of multi-dimensional repeated QOL data, that clinical parameters had significant effects on QOL in patients undergoing chemotherapy. Our findings suggest that supportive care to control non-hematological adverse events, especially gastrointestinal, could maintain overall QOL in cancer patients in an earlier phase of chemotherapy.

Aged↗
PubMed1987

ISMOD: an all-subsets regression program for generalized linear models. I. Statistical and computational background.

This paper describes a system written to carry out regression analyses under certain generalized linear models that are widely used in biomedical research. These include continuous response models such as the Weibull, log-logistic, log-normal and Cox proportional hazards models used in survival analysis, and also discrete Poisson, binomial and multinomial response regression models. The system fits models, generates residuals and other diagnostic output, and has an all-subsets regression feature. This paper describes the models implemented and gives statistical background; Part II describes the ISMOD system and presents examples of its application.

Biometry↗
PubMed1987

ISMOD: an all-subsets regression program for generalized linear models. II. Program guide and examples.

This paper describes a system written to carry out regression analyses under certain generalized linear models that are widely used in biomedical research. These include continuous response models such as the Weibull, log logistic, log normal and Cox proportional hazards models used in survival analysis, and also discrete Poisson, binomial and multinomial response regression models. The system fits models, generates residuals and other diagnostic output, and also has an all-subsets regression feature. This paper describes the ISMOD system and presents examples of its application; Part I describes the models implemented and gives statistical background.

Biometry↗
PubMed2003

Bayesian inference on order-constrained parameters in generalized linear models.

In biomedical studies, there is often interest in assessing the association between one or more ordered categorical predictors and an outcome variable, adjusting for covariates. For a k-level predictor, one typically uses either a k-1 degree of freedom (df) test or a single df trend test, which requires scores for the different levels of the predictor. In the absence of knowledge of a parametric form for the response function, one can incorporate monotonicity constraints to improve the efficiency of tests of association. This article proposes a general Bayesian approach for inference on order-constrained parameters in generalized linear models. Instead of choosing a prior distribution with support on the constrained space, which can result in major computational difficulties, we propose to map draws from an unconstrained posterior density using an isotonic regression transformation. This approach allows flat regions over which increases in the level of a predictor have no effect. Bayes factors for assessing ordered trends can be computed based on the output from a Gibbs sampling algorithm. Results from a simulation study are presented and the approach is applied to data from a time-to-pregnancy study.

Adult↗
PubMed1991

Changes initiated by a nursing supervision programme: an analysis based on log-linear models.

The paper discusses the effects of a nursing supervision programme on nursing practices, more specifically on how nurses take their patients' needs into account. The analysis is based on the need theory by Yura and Walsh and examines the changes initiated by the programme on the basis of the subjects' own experiences. The study was carried out in three Finnish public health care organizations. A total of 26 specially trained nurses took part in the supervision programme. The data were collected by a questionnaire immediately before and after the programme and, in order to evaluate long-term effects, 1 year later. Log-linear models were the main method of analysis. The results indicate that the programme had some very favourable effects. According to the nurses involved, their freedom of action and willingness to act, as well as nursing activity itself, had greatly improved. The change was most noticeable in the case of willingness to act. The nurses also felt that the programme had helped them to understand better the relationship between these three components. The results provide some useful clues with regard to the effects of nursing routines and the organization's nursing culture on the nurse's job and her activity.

Finland↗
PubMed1993

[Investigation of subjective symptoms among visual display terminal users and their affecting factors--analysis using log-linear models].

In order to evaluate factors affecting visual and musculoskeletal symptoms by visual display terminal (VDT) operation, a questionnaire survey was conducted among clerical workers in Chiba university. The results were as follows: 1) Of these workers, 81.9% engaged in VDT operation. For most of the subjective symptoms, the prevalence rates tended to increase with the degree of VDT use. 2) These complaints were combined to give visual and musculoskeletal symptom scores. Both of the scores were higher among females than males, and the musculoskeletal symptom score was significantly higher. No difference was found in regard to age. 3) Analysis using log-linear models was performed to evaluate the effects of sex and age. The results showed that the visual and musculoskeletal symptom scores were significantly higher among the workers operating VDTs for one or more hours per day than among those who did not operate them at all. Analysis of the effects of VDT workloads revealed that VDT use for five or more days per week significantly increased the prevalence rates of both symptoms. Their use for less than four days per week affected neither of the symptoms. With regard to operating time per day or length of VDT use, no differences were found. 4) This investigation suggested that the VDT workloads were not so heavy and that the effects on each symptom were minor among the subjects of the present survey. However, it is important that consideration be given to ensure that the workloads for workers who operate VDTs every day not be too heavy.

Adult↗
PubMed1998

Linear model of nitrogen balance and examination of the nature of true metabolisable energy and its nitrogen corrected form.

1. The nature of nitrogen (N) corrected true metabolisable energy (TMEN) was derived using a linear model of N balance, constructed from the relationship between excreted and ingested N. 2. TME was described in terms of a regression line, formed from 'fed' points relating energy voided to energy ingested (GE), as GE - (afed + bGE) + afast. On assignment of theoretical excreta and ingested energy components, a deviation from conceptual metabolisable energy (MEc), equal to the difference between afed and afast, was established and attributed to metabolic urinary energy (UmE). 3. The N balance model is based on the form of relationship between N excreted and N ingested (NI) that exhibits a linear deviation at 'initial' rates of N ingestion. The model postulates the following: The deviation is the result of a sparing effect of ingested N on the N component of UmE, viz. metabolic urinary N (UmN); The magnitude of UmN, through 'initial' values of fed N, is described by an intercept component, aNp, and a slope quantity, -(bNr - bNna) NI, where bNna and bNr are respectively the slopes of N excretion through 'initial' and 'subsequent' rates of ingested food N; The magnitude of the deviation from zero nitrogen balance (ZNB) through 'initial' and 'subsequent' rates of ingested N is the sum of the previous terms and aNm - (1 - bNr) NI, where aNm is the intercept component representing maintenance losses of N at fasting and (1-bNr) NI is the quantity of fed N retained to replace maintenance N loss. 4. Application of the appropriate energetic forms of UmN and aNm, viz. Et aNp - Et (bNr - bNna) NI and EuaNm, to the expression for obtaining TME, demonstrated that TME exceeded MEc by the quantities Et (bNr - bNna) NI and Et aNp, for test food intakes resulting in 'initial' and 'subsequent' rates of food N, respectively. 5. Application of appropriate energetic components of the model to simulate correction of TME to ZNB, demonstrated TMEZNB to be a biased quantity, deviating from MEc by the amount -Eu (1 - bNr) NI or expressed as an excreta energy slope component, [formula: see text] where Eu is an appropriate energy coefficient. An alternative perspective is that ZNB correction removes the energetic form of UmN as a source of bias, but introduces one related to EuaNm. Its nature may be perceived by regarding TME as a function of a regression line relating energy excreted (EE) to energy ingested that has been corrected for UmN energetic bias and is pivoting on a fulcrum vertically aligned with the position of ZNB on the GE (x) axis. The regression line rotates anti-clockwise in response to ZNB correction by an amount equal to the magnitude of EuaNm measured on the EE (y) axis from the point of interception. 6. The study identified processes that may be employed to remove bias and improve precision of TME.

Animals↗
PubMed1999

Exact test size and power of a Gaussian error linear model for an internal pilot study.

Wittes and Brittain recommended using an 'internal pilot study' to adjust sample size. The approach involves five steps in testing a general linear hypothesis for a general linear univariate model, with Gaussian errors. First, specify the design, hypothesis, desired test size, power, a smallest 'clinically meaningful' effect, and a speculated error variance. Second, conduct a power analysis to choose provisionally a planned sample size. Third, collect a specified proportion of the planned sample as the internal pilot sample, and estimate the variance (but do not test the hypothesis). Fourth, update the power analysis with the variance estimate to adjust the total sample size. Fifth, finish the study and test the hypothesis with all data. We describe methods for computing exact test size and power under this scenario. Our analytic results agree with simulations of Wittes and Brittain. Furthermore, our exact results apply to any general linear univariate model with fixed predictors, which is much more general than the two-sample t-test considered by Wittes and Brittain. In addition, our results allow for examination of the impact on test size of internal pilot studies for more complicated designs in the framework of the general linear model. We examine the impact of (i) small samples, (ii) allowing the planned sample size to decrease, (iii) the choice of internal pilot sample size, and (iv) the maximum allowable size of the second sample. All affect test size, power and expected total sample size. We present a number of examples including one that uses an internal pilot study in a three-group analysis of variance.

Analysis of Variance↗
PubMed2006

Determinants of hospital closure in South Korea: use of a hierarchical generalized linear model.

Understanding causes of hospital closure is important if hospitals are to survive and continue to fulfill their missions as the center for health care in their neighborhoods. Knowing which hospitals are most susceptible to closure can be of great use for hospital administrators and others interested in hospital performance. Although prior studies have identified a range of factors associated with increased risk of hospital closure, most are US-based and do not directly relate to health care systems in other countries. We examined determinants of hospital closure in a nationally representative sample: 805 hospitals established in South Korea before 1996 were examined-hospitals established in 1996 or after were excluded. Major organizational changes (survival vs. closure) were followed for all South Korean hospitals from 1996 through 2002. With the use of a hierarchical generalized linear model, a frailty model was used to control correlation among repeated measurements for risk factors for hospital closure. Results showed that ownership and hospital size were significantly associated with hospital closure. Urban hospitals were less likely to close than rural hospitals. However, the urban location of a hospital was not associated with hospital closure after adjustment for the proportion of elderly. Two measures for hospital competition (competitive beds and 1-Hirshman--Herfindalh index) were positively associated with risk of hospital closure before and after adjustment for confounders. In addition, annual 10% change in competitive beds was significantly predictive of hospital closure. In conclusion, yearly trends in hospital competition as well as the level of hospital competition each year affected hospital survival. Future studies need to examine the contribution of internal factors such as management strategies and financial status to hospital closure in South Korea.

Economics, Hospital↗
PubMed2004

Spectral-reflectance linear models for optical color-pattern recognition.

We propose a new method of color-pattern recognition by optical correlation that uses a linear description of spectral reflectance functions and the spectral power distribution of illuminants that contains few parameters. We report on a method of preprocessing color input scenes in which the spectral functions are derived from linear models based on principal-component analysis. This multichannel algorithm transforms the red-green-blue (RGB) components into a new set of components that permit a generalization of the matched filter operations that are usually applied in optical pattern recognition with more-stable results under changes in illumination in the source images. The correlation is made in the subspace spanned by the coefficients that describe all reflectances according to a suitable basis for linear representation. First we illustrate the method in a control experiment in which the scenes are captured under known conditions of illumination. The discrimination capability of the algorithm improves upon the conventional RGB multichannel decomposition used in optical correlators when scenes are captured under different illuminant conditions and is slightly better than color recognition based on uniform color spaces (e.g., the CIELab system). Then we test the coefficient method in situations in which the target is captured under a reference illuminant and the scene that contains the target under an unknown spectrally different illuminant. We show that the method prevents false alarms caused by changes in the illuminant and that only two coefficients suffice to discriminate polychromatic objects.

Journal Article↗