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PubMed2003

Statistical analysis of factors affecting fertilization rates and clinical outcome associated with intracytoplasmic sperm injection.

OBJECTIVE: To identify and evaluate the statistically significant predictors of intracytoplasmic sperm injection (ICSI) fertilization rates and clinical pregnancy in a single population using appropriate statistical techniques. DESIGN: Retrospective study. SETTING: Fertility and Endocrinology Center, University of Washington Medical Center, Seattle, Washington. PATIENT(S): Four hundred forty-one patients undergoing their first attempt at IVF-ICSI from January 1, 1999, to May 21, 2001. INTERVENTION(S): Each ICSI procedure for an individual patient was performed by a single operator. Sperm parameters, oocyte age, culture condition, ICSI technique, and ICSI operator were assessed as variables influencing the fertilization rate. We also assessed the impact of patient age, serum E(2) concentration on the day of hCG administration, embryo quality, and number of embryos transferred on the probability of achieving a clinical pregnancy. MAIN OUTCOME MEASURE(S): Fertilization rate and clinical pregnancy. RESULT(S): The 2 pronuclei (2PN) rate was significantly correlated with sperm motility, and there were significant differences in the 2PN rates among the ICSI operators. There was no difference in the 2PN rate among different sperm types or among the eight laboratory incubators or whether the eggs were cultured individually or in groups. Patient age, serum E(2) concentration on the day of hCG administration, embryo quality, and number of embryos transferred were all statistically significant predictors of clinical pregnancy. CONCLUSION(S): In our program, sperm motility and ICSI operator are the two most important predictors for the ICSI fertilization rate in vitro. Patient age, serum E(2) concentration on the day of hCG administration, embryo quality, and number of embryos transferred were all statistically significant predictors of clinical pregnancy.

Adult↗
PubMed2003

Trace element reference values in tissues from inhabitants of the EU. XII. Development of BioReVa program for statistical treatment.

Statistical data treatment is a key point in the assessment of trace element reference values being the conclusive stage of a comprehensive and organized evaluation process of metal concentration in human body fluids. The EURO TERVIHT project (Trace Elements Reference Values in Human Tissues) was started for evaluating, checking and suggesting harmonized procedures for the establishment of trace element reference intervals in body fluids and tissues. Unfortunately, different statistical approaches are being used in this research field making data comparison difficult and in some cases impossible. Although international organizations such as International Federation of Clinical Chemistry (IFCC) or International Union of Pure and Applied Chemistry (IUPAC) have issued recommended guidelines for reference values assessment, including the statistical data treatment, a unique format and a standardized data layout is still missing. The aim of the present study is to present a software (BioReVa) running under Microsoft Windows platform suitable for calculating the reference intervals of trace elements in body matrices. The main scope for creating an ease-of-use application was to control the data distribution, to establish the reference intervals according to the accepted recommendation, on the base of the simple statistic, to get a standard presentation of experimental data and to have an application to which further need could be integrated in future. BioReVa calculates the IFCC reference intervals as well as the coverage intervals recommended by IUPAC as a supplement to the IFCC intervals. Examples of reference values and reference intervals calculated with BioReVa software concern Pb and Se in blood; Cd, In and Cr in urine, Hg and Mo in hair of different general European populations.

Databases, Factual↗
PubMed2000

Spatial statistics and geographical information systems in epidemiology and public health.

This chapter surveys the principles behind spatial statistics and geographic information systems (GIS), and their application to epidemiology and public health. Like the other introductory chapters, it is aimed mainly to facilitate understanding in the chapters specific to certain diseases that follow, and to provide a short introduction to the field. A brief overview of spatial statistics and GIS is provided in the introduction. The sections that follow explore the ways in which we can map the distribution of disease, ways in which we can look for spatial patterns in the distribution of disease, and ways in which we can apply spatial statistics and GIS to the problem of identifying the causal factors of observed patterns. In the last section I discuss some of the ways in which these techniques have been applied to assist decision making for disease intervention, and conclude by discussing future developments in the field, and some of the issues surrounding the integration of spatial statistics and GIS.

Animals↗
PubMed2002

Statistical issues with microarrays: processing and analysis.

The study of gene expression with printed arrays and prefabricated chips is evolving from a qualitative to a quantitative science. Statistical procedures for determining quality control, differential expression, and reproducibility of findings are a natural consequence of this evolution. However, problems inherent to the technologies have raised important issues of how to apply adequate statistical tests. As a consequence, statistical approaches to microarray research are not yet as routine as they are in other sciences. Statistical methods, tailored to microarrays, continue to be adapted and developed. We present an overview of these methods and of outstanding issues in their use and validation.

Biometry↗
PubMed2004

[Quality analysis of the statistical used resources (material and methods section) in thesis projects of a university department].

INTRODUCTION AND OBJECTIVES: Studies about quality in thesis and investigation projects in biomedical sciences are unusual, but very important in university teaching because is necessary to improve the quality elaboration of the thesis. The objectives the study were to determine the project's quality of thesis in our department, according to the fulfillment of the scientific methodology and to establish, if it exists, a relation between the global quality of the project and the statistical used resources. MATERIAL AND METHODS: Descriptive study of 273 thesis projects performed between 1995-2002 in surgery department of the Zaragoza University. The review realized for 15 observers that they analyzed 28 indicators of every project. Giving a value to each of the indicators, the projects qualified in a scale from 1 to 10 according to the quality in the fulfillment of the scientific methodology. RESULTS: The mean of the project's quality was 5.53 (D.E: 1.77). In 13.9% the thesis projects was concluded with the reading of the work. The three indicators of statistical used resources had a significant difference with the value of the quality projects. DISCUSSION: The quality of the statistical resources is very important when a project of thesis wants to be realized by good methodology, because it assures to come to certain conclusions. In our study we have thought that more of the third part of the variability in the quality of the project of thesis explains for three statistical above-mentioned articles.

Academic Dissertations as Topic↗
PubMedDate not supplied

[The validity of infant mortality statistics in Navarra].

In order to explore the validity of official infant mortality statistics, the number of infant deaths registered in the cohort of live births and resident in Navarra (Spain) from 1985 to 1989, according to data supplied by the Department of Statistics of Navarra, has been compared with that obtained in a retrospective search into the information of the hospitals. Among 24,383 live births of the cohort, 291 were certified as infant deaths. An over-register of 13 cases (4.5%) and an under-register of 26 cases (8.9%) was detected. By excluding those live births with less than six months of gestation, as done by the National Institute of Statistics, the validity is altered, because apart from the errors mentioned, one must add those resulting from the incorrect filling-in of the "number of weeks pregnant"= variable. When correcting these deficiencies, the final statistics (Infant Mortality Risk = 11.17 per 1000 live births) did not differ much from the official figures (IMR = 11.48 per 1000 live births).

Birth Weight↗
PubMedDate not supplied

[An evaluation of the statistical significance and calculation of the confidence interval for the standardized mortality ratio].

The standardized mortality ratio (SMR) is the ratio of the number of deaths observed (D) to the number expected (E), on the basis of the mortality rates of some reference population. Several procedures have been proposed in order to test its significance and to estimate its confidence intervals. In this study, the SMR of two causes of death in 27 health areas of Castilla-La Mancha have been calculated. The significance has been evaluated by exact Poisson test and by four methods approximating the Poisson distribution by the normal: 1) a Z statistic based on the assumption that a Poisson variate with expectation E has a standard deviation equal to square root of E; 2) the Z statistic with a continuity correction; 3) a Z statistic based on the square root transformation of a Poisson variable and 4) an approximation of the exact test by Byar. Also, the confidence intervals have been estimated by exact method and by three approximate procedures: 1) by Byar; 2) by Z statistic uncorrected and 3) by the square root transformation of the Poisson distribution. With the exact methods and Byar procedure the results were very similar; therefore, using the last to testing significance and estimate the confidence intervals of SMR, is suggested.

Confidence Intervals↗
PubMed2001

Evaluating data from behavioral analysis: visual inspection or statistical models?

Traditional behavior analysis relies upon single-subject study designs and visual inspection of graphed data to evaluate the efficacy of experimental manipulations. Attempts to apply statistical inferential procedures to analyze data have been successfully opposed for many decades, despite problems with visual inspection and increasingly cogent arguments to utilize inferential statistics. In a series of experiments, we show that trained behavior analysts often identify level shifts in responding during intervention phases ('treatment effect') in modestly autocorrelated data, but trends are either misconstrued as level treatment effects or go completely unnoticed. Errors in trend detection illustrate the liabilities of using visual inspection as the sole means by which to analyze behavioral data. Meanwhile, because of greatly increased computer power and advanced mathematical techniques, previously undeveloped or underutilized statistical methods have become far more sophisticated and have been brought to bear on a variety of problems associated with repeated measures data. I present several nonparametric procedures and other statistical techniques to evaluate traditional behavioral data to augment, not replace, visual inspection procedures.

Journal Article↗
PubMed2001

Multivariate analysis of refractive data: mathematics and statistics of spherocylinders.

PURPOSE: To develop methods for multivariate statistical analysis of spherocylinders and to use these methods to compare autorefraction and manifest subjective refraction in 50 healthy eyes. SETTING: Department of Ophthalmology, Arhus University Hospital, Arhus, Denmark. METHODS: A method was developed to transform a spherocylinder to a suitable format as a spherical equivalent power (SEP) and 2 polar values, separated by an arch of 45 degrees, a so-called power-vector format. The accuracy of autorefraction was defined as the difference between autorefraction and manifest refraction, using the described power vector. These entities were subjected to multivariate analysis using the Hotelling T2 test. A method of graphic analysis was developed, using matrix algebra and computation of eigenvectors and eigenvalues. RESULTS: For individual data, the variation was considerably larger for the SEP than for the astigmatism. For aggregate data, univariate, bivariate, and trivariate statistical analysis did not demonstrate significant average differences between the 2 refraction methods. No refractive components and no combinations of refractive components displayed significant mean differences. CONCLUSIONS: The study confirmed our clinical experience that the astigmatism derived from autorefraction is nearly identical to manifest refraction, while the sphere needs some adjustment. In groups of healthy eyes, autorefraction can be used as a substitute for manifest refraction. Statistical analysis of spherocylinders, including evaluation of refractive procedures, can be performed in an exact manner with multivariate statistics.

Adolescent↗
PubMed2000

The interpretation and use of statistics in assisted reproductive technologies.

This article has discussed some of the uses and limitations of currently available statistics for ART programs. A well-known example from statistics states that flipping a coin will produce "heads" 50% of the time and "tails" 50% of the time, provided that the coin is flipped enough times. Experience also shows that the result of individual flips cannot be predicted. Similarly, in ART, statistics can only give general probabilities and not meaningful predictions of the outcome of any particular cycle. Patients should be aware of the limits of statistical analysis as it applies to their individual treatment.

Adult↗
PubMed2000

Adaptive, template moderated, spatially varying statistical classification.

A novel image segmentation algorithm was developed to allow the automatic segmentation of both normal and abnormal anatomy from medical images. The new algorithm is a form of spatially varying statistical classification, in which an explicit anatomical template is used to moderate the segmentation obtained by statistical classification. The algorithm consists of an iterated sequence of spatially varying classification and nonlinear registration, which forms an adaptive, template moderated (ATM), spatially varying statistical classification (SVC). Classification methods and nonlinear registration methods are often complementary, both in the tasks where they succeed and in the tasks where they fail. By integrating these approaches the new algorithm avoids many of the disadvantages of each approach alone while exploiting the combination. The ATM SVC algorithm was applied to several segmentation problems, involving different image contrast mechanisms and different locations in the body. Segmentation and validation experiments were carried out for problems involving the quantification of normal anatomy (MRI of brains of neonates) and pathology of various types (MRI of patients with multiple sclerosis, MRI of patients with brain tumors, MRI of patients with damaged knee cartilage). In each case, the ATM SVC algorithm provided a better segmentation than statistical classification or elastic matching alone.

Algorithms↗
PubMed2003

Conceptual, methodological, and statistical challenges in brain imaging studies of developmentally based psychopathologies.

Brain imaging studies in developmentally based psychopathologies most often use magnetic resonance imaging (MRI) to study regional volumes, task-related activity, neurometabolite concentrations, or the paths of fiber tracts within the brain. Methodological challenges for the use of MRI in studying these disorders include understanding the ultrastructural correlates of brain structure and function that are below the limits of resolution of this imaging modality and developing better methods for approximating the anatomical boundaries of the cytoarchitectonic units that are defined by those ultrastructural characteristics. Conceptual challenges include distinguishing findings that represent pathophysiologically central causes from compensatory and epiphenomenal effects, a difficulty that stems directly from the inherently correlational nature of imaging data. The promise of functional imaging studies must capitalize on the specificity of the cognitive and behavioral probes that are used to illuminate core features of the pathophysiology of developmental disorders, while recognizing the assumptions and limitations of the subtraction paradigms that are used to isolate the brain functions of interest. Statistical challenges include incorporating adequate statistical models for scaling effects within the brain, as well as modeling important demographic correlates that contribute to the substantial interindividual variability inherent in most imaging data. Statistical analyses need to consider the substantial intercorrelation of measures across the brain and the importance of correcting for multiple statistical comparisons, as well as the need for improved methods for brain warping and for assessing effective connectivity in functional imaging studies.

Brain↗
PubMed2003

Automated statistical analysis of protein abundance ratios from data generated by stable-isotope dilution and tandem mass spectrometry.

We describe an algorithm for the automated statistical analysis of protein abundance ratios (ASAPRatio) of proteins contained in two samples. Proteins are labeled with distinct stable-isotope tags and fragmented, and the tagged peptide fragments are separated by liquid chromatography (LC) and analyzed by electrospray ionization (ESI) tandem mass spectrometry (MS/MS). The algorithm utilizes the signals recorded for the different isotopic forms of peptides of identical sequence and numerical and statistical methods, such as Savitzky-Golay smoothing filters, statistics for weighted samples, and Dixon's test for outliers, to evaluate protein abundance ratios and their associated errors. The algorithm also provides a statistical assessment to distinguish proteins of significant abundance changes from a population of proteins of unchanged abundance. To evaluate its performance, two sets of LC-ESI-MS/MS data were analyzed by the ASAPRatio algorithm without human intervention, and the data were related to the expected and manually validated values. The utility of the ASAPRatio program was clearly demonstrated by its speed and the accuracy of the generated protein abundance ratios and by its capability to identify specific core components of the RNA polymerase II transcription complex within a high background of copurifying proteins.

Animals↗
PubMed1976

Statistical interpretation of fluorescence energy transfer measurements in macromolecular systems.

A statistical method is presented for the interpretation of intramolecular distance measurements by the fluorescence energy transfer technique in systems for which the detailed geometries of the donor-acceptor pairs are unknown. This method enables calculation of the probability that a specified distance range corresponds to the actual distance to be measured. It makes use of the numerically calculated probability density function for the distance of interest. The two general systems considered are the single donor-acceptor pair and the multi-donor-single-acceptor transfer. In both systems, the statistical method incorporates the uncertainty in the orientation of the donor and acceptor dipoles. In addition, it can take into account the rotational mobility of the donor dipoles determined by time-dependent emission anisotropy measurements. When more than one donor is involved in the transfer process, the uncertainties associated with the number and location of individual donors and the size and shape of the donor distribution are also incorporated in calculating the distance ranges. Application of the method was demonstrated for a wide range of transfer efficiency and Ro values for the single donor-acceptor system. Specific examples are also presented for interpretation of both single donor-acceptor and multi-donor-single-acceptor energy transfer measurements performed in order to reveal the spatial relationship of the sigma subunit and the rifampicin binding site in the Escherichia coli RNA polymerase (see Wu, C.-W., Yarbrough, L. R., Wu, F. Y.-H., and Hillel, Z. (1976), Biochemistry, preceding paper in this issue). Analysis of these energy transfer data by methods which use average values of the unknown geometrical parameters of the system yielded results similar to those obtained by the statistical method. However, the statistical method represents a more realistic approach to the interpretation of energy transfer measurements since it provides information concerning the entire range of possible distances and their relative likelihood.

Energy Transfer↗
PubMedDate not supplied

Prediction of polar surface area and drug transport processes using simple parameters and PLS statistics.

Modeling of the calculated polar surface area of drugs with rapidly derived descriptors (i.e., the number of hydrogen bonds accepting oxygen and nitrogen atoms and the number of hydrogen atoms bonded to these) using partial least squares projection to latent structures (PLS) analysis is described. The statistical analysis showed strong relationships between the hydrogen-bonding descriptors and the calculated polar surface area of five chemically diverse sets of drugs (R2>0.93 and Q2>0.69, n = 11, 20, 45, 70, and 74, respectively). The statistical models (using H-bonding descriptors and log P) of transport across Caco-2 cells (n = 11), brain-blood partitioning (two data sets, n = 45 and 70) and percent intestinal absorption (n = 20) showed R2 = 0.92, 0.72, 0.76, and 0.81 and Q2 = 0.74, 0.75, 0.71, and 0.73, respectively. The inclusion of log P improved two models, had no effect on one model, and had a slightly negative impact on one model. The combination of H-bonding descriptors with log P is similar to the Lipinski "rule-of-five" mnemonic. However, by using a multivariate statistical method (e.g., PLS), the prediction becomes quantitative instead of qualitative. Good statistical models were derived which permit fast computational screening and prioritization of virtual compound libraries.

Blood-Brain Barrier↗
PubMedDate not supplied

Information and organic molecules: structure considerations via integer statistics.

Information in relation to organic molecules was investigated in a previous work (Graham and Schacht, J. Chem. Inf. Comput. Sci. 2000, 40, 187). The topic is given further consideration here with the help of integer statistics. Discussed are the ramifications of an integer variable Omega(t) which quantifies the total number of binding complexions for an organic molecule. Offered is a statistical view of the maximum allowed number of independent regions D expressed by the molecule, dependent on Omega(t). We illustrate the distribution properties of D along with upper limit estimates of the regioinformation mu, also dependent on Omega(t). Integer statistics based on elementary number theory establish the key distribution properties of D and mu. In so doing, the traits distinguishing high regioinformation molecules are enumerated. The statistical approach encompasses all possible molecules and conditions, not just those reported to date in chemical databases. The aim is to view the regioinformation expressed by molecules in an alternative and general way.

Journal Article↗
PubMedDate not supplied

Development of novel statistical potentials describing cation-pi interactions in proteins and comparison with semiempirical and quantum chemistry approaches.

Novel statistical potentials derived from known protein structures are presented. They are designed to describe cation-pi and amino-pi interactions between a positively charged amino acid or an amino acid carrying a partially charged amino group and an aromatic moiety. These potentials are based on the propensity of residue types to be separated by a certain spatial distance or to have a given relative orientation. Several such potentials, describing different kinds of correlations between residue types, distances, and orientations, are derived and combined in a way that maximizes their information content and minimizes their redundancy. To test the ability of these potentials to describe cation-pi and amino-pi systems, we compare their energies with those computed with the CHARMM molecular mechanics force field and with quantum chemistry calculations at the Hartree-Fock level (HF) and at the second order of the Møller-Plesset perturbation theory (MP2). The latter calculations are performed in the gas phase and in acetone, in order to mimic the average dielectric constant of protein environments. The energies computed with the best of our statistical potentials and with gas-phase HF or MP2 show correlation coefficients up to 0.96 when considering one side-chain degree of freedom in the statistical potentials and up to 0.94 when using a totally simplified model excluding all side-chain degrees of freedom. These potentials perform as well as, or better than, the CHARMM molecular mechanics force field that uses a much more detailed protein representation. The good performance of our cation-pi statistical potentials suggests their utility in protein structure and stability prediction and in protein design.

Algorithms↗
PubMedDate not supplied

Statistical mechanical treatment of protein conformation. 4. A four-state model for specific-sequence copolymers of amino acids.

One-dimensional short-range interaction models for specific-sequence copolymers of amino acids are being developed in this series of papers. In this paper, our earlier three-state model [involving helical (h), extended (epsilon), and coil (or other) (c) states] is extended to a four-state model by preserving the h and epsilon states, introducing the chain-reversal state (R and S), and redefining the c state. This model involves six parameters (wh, vh, vepsilon, vR, vS, and uc) and requires a 6 X 6 statistical weight matrix. A nearest-neighbor approximation of the four-state model is also formulated; it requires a 5 X 5 matrix, involving the same six parameters. By expressing the statistical weights relative to that of the epsilon state, only five parameters (wh, vh, vR, vS, and uc) are required in both the 6 X 6 and 5 X 5 matrices. The statistical weights for the four-state model are evaluated from the atomic coordinates of the x-ray structures of 26 native proteins. These statistical weights, and the four-state model, are used to develop a procedure to predict the backbone conformations of proteins. Since the prediction of helical and extended conformations is carried out by the procedure described in papers 1-3 of this series, we focus particular attention on chain-reversal conformations in this paper. The conformational-sequence probabilities of finding a residue in h, epsilon, R, S, or c states, and of finding two consecutive residues in a chain-reversal conformation, defined as relative values with respect to their average values over the whole molecule, are calculated for 23 proteins. By comparing these conformational-sequence probabilities to experimental X-ray observations, it was found that, in addition to the prediction of helical and extended conformations (reported in paper 3), 219 chain-reversal regions out of 372 observed by x-ray diffraction studies of 23 proteins were predicted correctly. These results suggest that the assumption of the dominance of short-range interactions in determining chain-reversal (as well as helical or extended) conformations in proteins, on which the predictive scheme is based, is a reasonable one. Finally, in the Appendix, the property of asymmetric nucleation of helical sequences is introduced into the (nearest-neighbor) four-state model.

Amino Acid Sequence↗