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PubMed1995

A voxel-based method for the statistical analysis of gray and white matter density applied to schizophrenia.

We describe a novel technique for characterizing regional cerebral gray and white matter differences in structural magnetic resonance images by the application of methods derived from functional imaging. The technique involves automatic scalp-editing of images followed by segmentation, smoothing, and spatial normalization to a symmetrical template brain in stereotactic Talairach space. The basic idea is (i) to convert structural magnetic resonance image data into spatially normalized images of gray (or white) matter density, effected by segmenting the images and smoothing, and then (ii) to use Statistical Parametric Mapping to make inferences about the relationship between gray (or white) matter density and symptoms (or other pathophysiological measures) in a regionally specific fashion. Because the whole brain sum of gray (or white) matter indices is treated as a confound, the analysis reduces to a characterization of relative gray (or white) matter density on a voxel by voxel basis. We suggest that this is a powerful approach to voxel-based statistical anatomy. Using the technique, we constructed maps of the regional cerebral gray and white matter density correlates of syndrome scores (distinct psychotic symptoms) in a group of 15 schizophrenic patients. There was a negative correlation between the score for the reality distortion syndrome and regional gray matter density in the left superior temporal lobe (P = 0.01) and regional white matter density in the corpus callosum (P < 0.001). These abnormalities may be associated with functional changes predisposing to auditory hallucinations and delusions. This method permits the detection of structural differences within the entire brain (as opposed to selected regions of interest) and may be of value in the investigation of structural gray and white matter abnormalities in a variety of brain diseases.

Adult↗
PubMed2003

Evaluation of methodology for detection of genetic bottlenecks: inferences from temporally replicated lake trout populations.

Statistical methods have been proposed to detect recent bottlenecks on the basis of genetic characterizations of natural populations. In the absence of direct estimates of contemporary or historical population numbers, we tested the indirect M-ratio method based on microsatellite motif size frequency profiles using three historical and three contemporary Great Lakes populations of Salvelinus namaysuch for which severe reductions in population numbers are documented. Simulations employing plausible ranges of empirical population parameter values were used to explore bottleneck likelihood surfaces. We show that single values of the M-ratio are not sufficient to unambiguously infer a bottleneck without knowledge of mutation rates and effective population size (i.e., 4Ne mu or [symbol: see text]). Inferences of the degree of population bottleneck would be best supported if analyses were conducted across plausible ranges of [symbol: see text] and by qualitative comparisons among population samples.

Animals↗
PubMedDate not supplied

Impact of the integrated Radio Communication Project in Nepal, 1994-1997.

The Radio Communication Project (RCP) in Nepal is an ongoing, theory-based, multimedia reproductive health campaign which began in 1995. It consists of two entertainment-education radio serials (a soap opera for the general public and a dramatized distance education serial for health workers), additional radio spot advertisements and promotions, and complementary print materials. This paper examines impact data from a variety of sources, including a pre- and postpanel survey of currently married women (N = 1905), three waves of clinic-based observations of client-provider interactions (N = 240 per wave) and client exit interviews (N = 240 per wave), and 2 years of clinic service statistics, in order to draw inferences about the separate and combined effects of the RCP components. The study found increased health worker interpersonal interaction skills, improved quality of client-provider interactions, increased client self-efficacy in dealing with health workers, improved client attitudes toward health services and toward the practice of family planning, increased adoption of family planning, and increased family planning service utilization, all attributable to the RCP. The panel data allowed statistical control of the influence of predisposing factors before the campaign on postcampaign ideation and behavior. The effect of the RCP on contraceptive behavior was largely indirect through its influence on ideation. Implications for the design of integrated, multimedia, entertainment-education campaigns and integrated evaluation designs are discussed.

Female↗
PubMed1981

Statistical analysis of an attitude scale to measure patient satisfaction with medical care.

Patient satisfaction with medical care is concept that is viewed as important to consider but difficult to measure. The most widely reported and most standardized measure of patient attitudes toward medical care is the scale developed by Hulka et al. The purpose of this article is first to present the results of three separate administrations of this scale and, second, to detail the statistical analysis performed using these data sets. The results of these three administrations show remarkable similarity of results, thus leading to an inference of high reliability. Through the statistical analysis of the validity of the scale, however, it is demonstrated that further work is needed before the attitude scale can be generally used. The three phases of the statistical analysis include an item analysis, a Guttman scalogram analysis and a factor analysis. The results of these three validity analyses do not support the attitude scale in its current form. The result of this work leads us to conclude that this attitude scale is not ready to be used in a community setting for predictive purposes, as has been suggested. Our results indicate that further revision and analysis are necessary before we can approach a valid as well as reliable attitude scale to measure patient satisfaction with medical care. Although this suggests the need for extensive theoretical research, the effort is clearly worthwhile, as a valid and reliable measurement of patient satisfaction will provide us with invaluable insights into the process of health care delivery.

Consumer Behavior↗
PubMed2001

Comparing personal trajectories and drawing causal inferences from longitudinal data.

This review considers statistical analysis of data from studies that obtain repeated measures on each of many participants. Such studies aim to describe the average change in populations and to illuminate individual differences in trajectories of change. A person-specific model for the trajectory of each participant is viewed as the foundation of any analysis having these aims. A second, between-person model describes how persons very in their trajectories. This two-stage modeling framework is common to a variety of popular analytic approaches variously labeled hierarchical models, multilevel models, latent growth models, and random coefficient models. Selected published examples reveal how the approach can be flexibly adapted to represent development in domains as diverse as vocabulary growth in early childhood, academic learning, and antisocial propensity during adolescence. The review then considers the problem of drawing causal inferences from repeated measures data.

Adolescent↗
PubMed2006

Forward inference using functional neuroimaging: dissociations versus associations.

Many people are excited by functional neuroimaging as a new tool for cognitive science; many others are sceptical. In this opinion article, I describe a 'forward inference' that one can make from patterns of brain activity to distinguish between cognitive theories. I give an example of forward inferences in research on recognition memory, and outline some statistical criteria for a 'qualitative difference' in brain activity. Forward inferences resemble the dissociation logic long-used in behavioural studies of healthy and brain-damaged people, although I argue that dissociations in neuroimaging data can go beyond behavioural dissociations. Nonetheless, forward inferences are only as good as the cognitive theories to which they pertain, and are most valuable in conjunction with other types of inference.

Association↗
PubMed2003

A cautionary note on exact unconditional inference for a difference between two independent binomial proportions.

Fisher's exact test for comparing response proportions in a randomized experiment can be overly conservative when the group sizes are small or when the response proportions are close to zero or one. This is primarily because the null distribution of the test statistic becomes too discrete, a partial consequence of the inference being conditional on the total number of responders. Accordingly, exact unconditional procedures have gained in popularity, on the premise that power will increase because the null distribution of the test statistic will presumably be less discrete. However, we caution researchers that a poor choice of test statistic for exact unconditional inference can actually result in a substantially less powerful analysis than Fisher's conditional test. To illustrate, we study a real example and provide exact test size and power results for several competing tests, for both balanced and unbalanced designs. Our results reveal that Fisher's test generally outperforms exact unconditional tests based on using as the test statistic either the observed difference in proportions, or the observed difference divided by its estimated standard error under the alternative hypothesis, the latter for unbalanced designs only. On the other hand, the exact unconditional test based on the observed difference divided by its estimated standard error under the null hypothesis (score statistic) outperforms Fisher's test, and is recommended. Boschloo's test, in which the p-value from Fisher's test is used as the test statistic in an exact unconditional test, is uniformly more powerful than Fisher's test, and is also recommended.

Humans↗
PubMed2000

Locomotion and proliferation of glioblastoma cells in vitro: statistical evaluation of videomicroscopic observations.

OBJECT: The motility and doubling of human glioblastoma cells were investigated by means of statistical evaluation of large sets of data obtained using computer-aided videomicroscopy. METHODS: Data were obtained on cells in four established glioblastoma cell lines and also on primary tumor cells cultured from fresh surgical samples. Growth rates and cell cycle times were measured in individual microscopic fields. The averages of cell cycle time and the duplication time for the recorded cell populations were 26.2 +/- 5.6 hours and 38 +/- 4 hours, respectively. With these parameters, no significant differences among the cell lines were revealed. Also, there was no correlation in the cell cycle time of a parent cell and its progeny in any of the cultures. Statistical analysis of cell locomotion revealed an exponential distribution of cell velocities and strong fluctuations in individual cell velocities across time. The average velocity values ranged from 4.2 to 27.9 micro/hour. In spite of the uniform histopathological classification of the four tumors, each cell line produced by these tumors displayed distinct velocity distribution profiles and characteristic average velocity values. A comparison of recently established primary cultures with cell lines that had propagated multiple times indicated that cells derived from different tumors sustain their characteristic locomotor activity after several passages. CONCLUSIONS: It can be inferred from the data that statistical evaluation of physical parameters of cell locomotion can provide additional tools for tumor diagnosis.

Brain Neoplasms↗
PubMed1999

Ecological inference.

Ecological inference is the process of drawing conclusions about individual-level behavior from aggregate-level data. Recent advances involve the combination of statistical and deterministic means to produce such inferences.

Behavior↗
PubMedDate not supplied

Factors influencing nurses' inferences about patient pain.

This study examined the factors that influence nurses' perception of patient pain. Sixteen vignettes were constructed on the basis of interviews with nurses about factors affecting their perception of patient pain and previous published literature. Four variables were systematically varied within a factorial design: diagnosis (surgery vs oncology), level of patient mobility, presence or absence of physical and behavioural signs, and patient gender. Twenty-seven nurses rated each vignette for degree of inferred patient pain and degree of patient psychological distress. Mobility and positive signs of pain had statistically significant effects on nurses' judgments of inferred pain (P < 0.001), but diagnosis had no main effect. Significant interactions showed that: inferred pain in male patients was seen to be greater when immobile while mobility had no effect on the inferred pain of female patients (P < 0.003); oncology patients (compared with surgical patients) had greater inferred pain when displaying positive signs (P < 0.024); and positive signs yielded higher ratings where patients were immobile (P < 0.001). Female patients were perceived to experience higher psychological distress than men (P < 0.037) and oncology patients were perceived to experience higher distress than surgical patients (P < 0.005). Ratings of perceived pain and distress were significantly correlated but did not differ in magnitude. Offered a choice of analgesics to relieve pain for each of the patients depicted, nurses typically chose those with the lowest strength.

Attitude of Health Personnel↗
PubMed2005

High variation in developmental instability under non-normal developmental error: a Bayesian perspective.

The developmental mechanisms behind developmental instability (DI) are only poorly understood. Nevertheless, fluctuating asymmetry (FA) is often used a surrogate for DI. Based on statistical arguments it is often assumed that individual levels of FA are only weakly associated with the underlying DI. Patterns in FA therefore need to be interpreted with caution, and should ideally be transformed into patterns in DI. In order to be able to achieve that, assumptions about the distribution of developmental errors must be made. Current models assume that errors during development are additive and independent such that they yield a normal distribution. The observation that the distribution of FA is often leptokurtic has been interpreted as evidence for between-individual variation in DI. This approach has led to unrealistically high estimates of between-individual variation in DI, and potentially incorrect interpretations of patterns in FA, especially at the individual level. Recently, it has been suggested that the high estimates of variation in DI may be biased upward because either developmental errors are log-normal or gamma distributed and/or low measurement resolution of FA. A proper estimation of the amount (and shape) of heterogeneity in DI is crucial for the interpretation of patterns in FA and their transformation into patterns in DI. Yet, incorrect model assumptions may render misleading inferences. We therefore develop a statistical model to evaluate the sensitivity of results under the normal error model against the two alternative distributions as well as to investigate the importance of low measurement resolution. An analysis of simulated and empirical data sets indicated that bias due to misspecification of the developmental error distribution can be substantial, yet, did not appear to reduce estimates of variation in DI in empirical data sets to a large extent. Effects of low measurement resolution were neglectable. The importance of these results are discussed in the context of the interpretation of patterns in FA.

Animals↗
PubMed1998

Split support and split conflict randomization tests in phylogenetic inference.

Randomization tests allow the formulation and statistical testing of null hypotheses about the quality of entire data sets or the quality of fit between the data and particular phylogenetic hypotheses. Randomization tests of phylogenetic hypotheses based on the concepts of split support and split conflict are described here, as are tests where splits, rather than the data, are randomly permuted. These tree-independent randomization tests are explored through their application to phylogenetic data for caecilian amphibians. Of these tests, split support randomization tests appear to be the most promising tools for phylogeneticists. These tests seem quite conservative, are applicable to nonpolar data and unordered multistate characters, and do not have the problems of nonindependence that affect split conflict and hierarchy tests. Unlike split conflict tests, their power does not appear to be correlated with split size. However, all tests are sensitive to taxonomic scope. Split support tests may help discern data that are likely to be affected by the problems of long-branches effects. Comparison of test results for mutually incompatible splits may help identify the presence of strong misleading signals in phylogenetic data. Significant split support could be a prerequisite for considering phylogenetic hypotheses to be well supported by the data, and split support randomization tests might be usefully applied prior to or as part of tree construction.

Amphibians↗
PubMed1999

Resampling and multiplicity in cost-effectiveness inference.

We compare published methods for placing statistical confidence limits around incremental cost-effectiveness ratio statistics and show that only a nonparametric, bootstrap approach using polar angles gives completely reasonable results when neither treatment has significant advantages in cost or effectiveness. We also discuss alternative ways to report analytical results using plots, confidence or tolerance limits, and quadrant acceptability fractions. Finally, we use simulation to study the multiplicity bias that can be introduced into ICER confidence limits when only the most favorable results are reported over several possible choices of numerator cost measure and denominator effectiveness measure.

Confidence Intervals↗
PubMed1995

Macroevolutionary inferences from primate phylogeny.

We apply new statistical methods to a recent estimate of the phylogeny of all living primate species to test a range of models of cladogenesis. Null models in which probabilities of speciation and extinction do not differ among contemporaneous lineages are not consistent with the phylogeny. We present evidence that the net rate of cladogenesis (speciation rate minus extinction rate) increased in the lineage leading to the Cercopithecidae (Old World monkeys), and that there have been further increases in some lineages within that family. Such increases suggest the occurrence of clade selection, although we have not identified the selected trait or traits. There is no evidence that the net rate of cladogenesis is a function either of how many primate lineages are already present or of time. Intriguingly, three other clades--Strepsirhini, Platyrrhini and Hominoidea--appear to have had very similar rates of clade growth, in spite of their great biological differences.

Animals↗
PubMed2005

Advanced statistics: bootstrapping confidence intervals for statistics with "difficult" distributions.

The use of confidence intervals in reporting results of research has increased dramatically and is now required or highly recommended by editors of many scientific journals. Many resources describe methods for computing confidence intervals for statistics with mathematically simple distributions. Computing confidence intervals for descriptive statistics with distributions that are difficult to represent mathematically is more challenging. The bootstrap is a computationally intensive statistical technique that allows the researcher to make inferences from data without making strong distributional assumptions about the data or the statistic being calculated. This allows the researcher to estimate confidence intervals for statistics that do not have simple sampling distributions (e.g., the median). The purposes of this article are to describe the concept of bootstrapping, to demonstrate how to estimate confidence intervals for the median and the Spearman rank correlation coefficient for non-normally-distributed data from a recent clinical study using two commonly used statistical software packages (SAS and Stata), and to discuss specific limitations of the bootstrap.

Confidence Intervals↗
PubMedDate not supplied

[The role of age, smoking habits, and oral contraceptives in the frequency of myocardial infarction in young women (author's transl)].

Owing to the discussion aroused by different papers which have appeared in the last few years on the possible side-effects of oral contraceptives, an examination is made in this paper of the methods used in some of these studies, trying to elucidate to what extent we can trust the conclusions obtained, in order to decide whether oral contraceptives, by themselves, are a real and considerable risk to women's health, and analysing the role of oral contraceptives associated with other risk factors which can influence the frequency of myocardial infarction in young women. It is concluded that the use of oral contraceptives does not represent a statistically significant risk and, therefore, a causal inference cannot be attributed to them; but there exist other risk factors which prove to be of statistically demonstrable danger for myocardial infarction, such as smoking and obesity. Also, it seems evident that the combined effect of smoking and oral contraceptive use is synergistic. However, even though these two factors associated can increase the risk of myocardial infarction, we must not dismiss the possibility of this increment being influenced by other, equally logical circumstances.

Adult↗
PubMed1993

A unified approach to study hypervariable polymorphisms: statistical considerations of determining relatedness and population distances.

Relatedness between individuals as well as evolutionary relationships between populations can be studied by comparing genotypic similarities between individuals. When hypervariable loci are used to describe genotypes, it is shown that both of these problems can be approached with a unified theory based on allele sharing between individuals. The distributions of the number of shared alleles between individuals indicate their kin relationships. Extending this, we obtain statistics for genetic distances between populations based on average number of alleles shared between individuals within and between two different populations. Traditional statistical inferential procedure can be used to establish specific kinship relationships between individuals. We derive estimates of the number of hypervariable loci needed for a specified reliability of such an inference. Evolutionary dynamics of genetic distance statistics based on allele sharing is also studied. It shows that such measures of genetic distances remain linear with the time of divergence for a period comparable to that of the gene frequency-based measures of genetic distances. Statistical properties of measures based on allele sharing establish that for using such summary statistics it is not necessary to know the full characteristics of all loci used. It is enough to know the degree of heterozygosity per locus and the number of loci. Therefore, in principle, this approach can also be used for DNA fingerprinting data in the studies of relatedness between individuals as well as between populations. The possible compromising features of multilocus DNA fingerprinting data are also discussed.

Alleles↗
PubMed1982

Economic cycles and health. Towards a sociological understanding of the impact of the recession on health and illness.

Does the impact of large scale and long term unemployment have a negative influence on the health of a community? This paper critically examines research evidence at a macro and micro level of analysis debating the major theoretical issues, and the difficulty in establishing causality between changing mortality patterns over time and fluctuations in the business cycle. It is argued that macro analysis cannot stand on its own as an explanation but needs to be combined with an understanding of the career progression of the unemployed and the stages of psychological transition that occur to bridge the gap between macro and micro environments, and give some understanding of the changes in health status that may be observed in a population following a period of unemployment or economic uncertainty. Both quantitative and qualitative research suggest that not only is the health of those actually at risk but also their immediate family and the community at large during a recession. From this proposition two significant factors emerge in the literature which could explain the association between unemployment rates and changing patterns of mortality. Firstly stress is highlighted in most of the research reviewed, and could be the linking factor for material reasons and also those of social well being. Secondly health status, like that of unemployment is not equally shared in the United Kingdom community, but rather shouldered on a class basis, the most consistent finding being an inverse relationship between economic status and mortality placing the burden squarely on the lower social economic groups who are most vulnerable to unemployment. Taken together all the evidence suggests the inferences made from the macro statistics despite the difficulties in demonstrating causality, suggesting a strong link between mortality rates and cycles of economic activity.

Adult↗