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At least 1,693 records · Page 94Linked to original sources
PubMed2002

Statistical analysis of the nursing minimum data set for The Netherlands.

The purpose of this overview is to examine and illustrate the feasible options for the statistical analysis of nursing minimum data sets (NMDSs). After explaining the need for these data collections, examples from different countries are discussed and examples of the methods used for statistical analysis are summarized. Distinct purposes for information uses and for the presentation of information requires different approaches for data collection and statistical analysis. The feasible options for the nursing minimum data set for the Netherlands (NMDSN) have been described to illustrate the different methods available. Six studies are discussed, illustrating their goals, data collection methods, data analysis, and results. These studies include visualizing nursing care by means of frequencies of nursing diagnoses and interventions, RIDIT (relative to an identified distribution) analysis, fingerprints, and graphs from multidimensional scaling techniques. In addition, using data sets for workload measurement and testing of instruments is presented. The overview ends with general recommendations for data collection and analysis of NMDSs.

Data Collection↗
PubMed2006

An appeal for statistical rigour.

Following recent comments by Jean Cohen in this journal, this short note is yet another appeal for a higher standard of statistical analysis in Assisted Reproduction Research. In order to avoid the conflicts and contradictions highlighted by Jean Cohen, it is imperative that the highest standards of numerical evaluation are maintained. To this end, research workers are urged to recruit statisticians to assist in the analysis and interpretation of their results, and in the preparation of their manuscripts. Statistical science is held in rather low esteem in many quarters, a situation that is aggravated by the publicity attached to contradictory findings. A higher standard of statistical analysis is required to restore the subject's standing among research workers.

Humans↗
PubMed2001

Comparison of statistical power between 2 * 2 allele frequency and allele positivity tables in case-control studies of complex disease genes.

In case-control studies of complex disease genes, allele frequencies or allele positivities at candidate loci or markers are compared between cases and controls. Although 2 x 2 contingency tables based on allele frequency and allele positivity are generally used to perform simple statistical tests (e.g. a comparison of two proportions and a chi2 test), little is known about the difference in power between the two tables. In this study, we investigated the number of subjects required to obtain a power of 1-beta with a significance level of alpha for the allele frequency and allele positivity tables. A large difference in the required number of subjects was found between the two tables. Allele positivity tables were suitable for the detection of susceptibility alleles showing a dominant mode of inheritance (MOI). On the other hand, allele frequency tables were suitable for the identification of susceptibility alleles showing a recessive MOI or a multiplicative MOI. In the case of an additive MOI, a suitable table was determined by combining the frequency of the susceptibility allele and the penetrance. These results imply that there are cases in which true association is detected based on one contingency table and is not detected based on another. A simulation analysis revealed that the type I error rate was not much inflated under the null hypothesis of no association, even when a statistical test was performed twice using both allele frequency and allele positivity tables. In contrast, under the alternative hypothesis, the loss of power was marked when a test was performed once using an unsuitable table. In conclusion, statistical tests should be performed using both tables, without adjustment of multiplicity, in case-control studies of complex disease genes when the study objective is exploratory.

Alleles↗
PubMed2001

Statistical design and the analysis of gene expression microarray data.

Gene expression microarrays are an innovative technology with enormous promise to help geneticists explore and understand the genome. Although the potential of this technology has been clearly demonstrated, many important and interesting statistical questions persist. We relate certain features of microarrays to other kinds of experimental data and argue that classical statistical techniques are appropriate and useful. We advocate greater attention to experimental design issues and a more prominent role for the ideas of statistical inference in microarray studies.

Analysis of Variance↗
PubMed2000

Discrimination of the notifiable pathogen Gyrodactylus salaris from G. thymalli (Monogenea) using statistical classifiers applied to morphometric data.

The identification and discrimination of 2 closely related and morphologically similar species of Gyrodactylus, G. salaris and G. thymalli, were assessed using the statistical classification methodologies Linear Discriminant Analysis (LDA) and k-Nearest Neighbours (KNN). These statistical methods were applied to morphometric measurements made on the gyrodactylid attachment hooks. The mean estimated classification percentages of correctly identifying each species were 98.1% (LDA) and 97.9% (KNN) for G. salaris and 99.9% (LDA) and 73.2% (KNN) for G. thymalli. The analysis was expanded to include another 2 closely related species and the new classification efficiencies were 94.6% (LDA) and 98.% (KNN) for G. salaris; 98.2% (LDA) and 72.6% (KNN) for G. thymalli; 86.7% (LDA) and 91.8% (KNN) for G. derjavini; and 76.5% (LDA) and 77.7% (KNN) for G. truttae. The higher correct classification scores of G. salaris and G. thymalli by the LDA classifier in the 2-species analysis over the 4-species analysis suggested the development of a 2-stage classifier. The mean estimated correct classification scores were 99.97% (LDA) and 99.99% (KNN) for the G. salaris-G. thymalli pairing and 99.4% (LDA) and 99.92% (KNN) for the G. derjavini-G. truttae pairing. Assessment of the 2-stage classifier using only marginal hook data was very good with classification efficiencies of 100% (LDA) and 99.6% (KNN) for the G. salaris G. thymalli pairing and 97.2% (LDA) and 99.2% (KNN) for the G. derjavini-G. truttae pairing. Paired species were then discriminated individually in the second stage of the classifier using data from the full set of hooks. These analyses demonstrate that using the methods of LDA and KNN statistical classification, the discrimination of closely related and pathogenic species of Gyrodactylus may be achieved using data derived from light microscope studies.

Animals↗
PubMed1976

Issues in the development of statistical and epidemiological data for mental health services research.

The planning of health services consists of a process that generally involves the following steps: (a) situational analysis, or the description, definition and statement of the problem, its characteristics and dimensions in relation to population and time; (b) the formulation of alternative tactical approaches to the handling and solution of the problem; (c) decision analysis or the selection of a plan; (d) discussion and implementation of the plan selected; (e) evaluation of the results achieved in relation to the problem, situations or populations concerned. This paper discusses the content of a programme of mental health services research for collecting and analysing the information needed to apply these processes to the planning of mental health services, monitoring the manner in which the plan is being implemented, and assessing its effectiveness in achieving short-term and intermediate objectives and long-term goals. Statistical and epidemiological information play an important role in these processes, particularly in the situational analysis and the evaluation processes. Illustrations have been provided of types of data that are produced in the national mental health statistics programme in the United States. Difficulties in using such data to answer questions concerning the needs for mental health services, and manpower requirements for delivering services to meet these needs are discussed. In many instances, currently available data are quite inadequate for answering key issues such as these, plus others related to living arrangements of the population, the effect of services on the persons who receive them, their families and the communities in which they live. Thus, much still remains to be done to develop systematic, comparative morbidity statistics on the incidence, duration and prevalence of mental disorders in the general population, on the needs for mental health services, and on the effectiveness of our efforts to prevent disorders that can be prevented, and to reduce the amount of disability and distress caused by those that cannot be prevented or terminated. A series of problems have been identified, the solutions to which would assist materially in providing data that would narrow gaps between available knowledge and that which is needed. The importance of establishing well-staffed research units at the catchment area level with stable funding to accomplish this is underscored. It is a matter of the greatest urgency that adequate resources--financial, manpower, scientific and administrative--be made available to solve these problems. If this is not done, then effordts to document quantitatively the effectiveness of programmes to prevent and control mental disorders will continue to suffer from many of the same shortcomings that have impeded our past and continue to impede current efforts to accomplish this.

Adolescent↗
PubMed1982

Statistical tests in experimental psychiatric research.

It is pointed out that the subjects used in psychiatric research experiments are usually drawn in such a way as to invalidate many of the commonly applied statistical tests. The necessarily non-statistical component of any inference is noted, and the area where one might hope for an exact statistical inference is identified. A class of tests permitting such inferences is described. Their theoretical and practical advantages are outlined.

Humans↗
PubMed2005

A model-adjusted space-time scan statistic with an application to syndromic surveillance.

The space-time scan statistic is often used to identify incident disease clusters. We introduce a method to adjust for naturally occurring temporal trends or geographical patterns in illness. The space-time scan statistic was applied to reports of lower respiratory complaints in a large group practice. We compared its performance with unadjusted populations from: (1) the census, (2) group-practice membership counts, and on adjustments incorporating (3) day of week, month, and holidays; and (4) additionally, local history of illness. Using a nominal false detection rate of 5%, incident clusters during 1 year were identified on 26, 22, 4 and 2% of days for the four populations respectively. We show that it is important to account for naturally occurring temporal and geographic trends when using the space-time scan statistic for surveillance. The large number of days with clusters renders the census and membership approaches impractical for public health surveillance. The proposed adjustment allows practical surveillance.

Censuses↗
PubMed2005

Maximizing statistical power in group-randomized vaccine trials.

Statistical power in group-randomized vaccine trials is complex: group randomization may increase power by capturing more transmission effects but may decrease power as more individuals are affected by a common source of variance. The former effect dominates when most infections arise from within the group and the latter when most arise outside. This process is complicated further when individuals possess partial natural immunity. Vaccine trials typically compare infection frequency (as measured by agent or antibody detection) in vaccinated vs. unvaccinated groups. To assess the relative contributions to statistical power by direct agent detection vs. serological detection of recent infection, we constructed stochastic compartmental models using differential equations describing all possible discrete states of the group. We contrasted models where natural immunity was absent, altered only the susceptible state, or altered both the susceptible and infected states. We observed the effects of endemic infection levels, the fraction of infection arising from outside the group, infectiousness vs. susceptibility vaccine effects and waning rates. There was significant enhancement of statistical power when serological testing separated infected and susceptible classes into subsets by natural immunity status.

Haemophilus Infections↗
PubMed1998

The design and analysis of longitudinal studies of development and psychopathology in context: statistical models and methodological recommendations.

The utility and flexibility of recent advances in statistical methods for the quantitative analysis of developmental data--in particular, the methods of individual growth modeling and survival analysis--are unquestioned by methodologists, but have yet to have a major impact on empirical research within the field of developmental psychopathology and elsewhere. In this paper, we show how these new methods provide developmental psychopathologists with powerful ways of answering their research questions about systematic changes over time in individual behavior and about the occurrence and timing of life events. In the first section, we present a descriptive overview of each method by illustrating the types of research questions that each method can address, introducing the statistical models, and commenting on methods of model fitting, estimation, and interpretation. In the following three sections, we offer six concrete recommendations for developmental psychopathologists hoping to use these methods. First, we recommend that when designing studies, investigators should increase the number of waves of data they collect and consider the use of accelerated longitudinal designs. Second, we recommend that when selecting measurement strategies, investigators should strive to collect equatable data prospectively on all time-varying measures and should never standardize their measures before analysis. Third, we recommend that when specifying statistical models, researchers should consider a variety of alternative specifications for the time predictor and should test for interactions among predictors, particularly interactions between substantive predictors and time. Our goal throughout is to show that these methods are essential tools for answering questions about life-span developmental processes in both normal and atypical populations and that their proper use will help developmental psychopathologists and others illuminate how important contextual variables contribute to various pathways of development.

Adolescent↗
PubMed2003

A method for assessing the statistical significance of mass spectrometry-based protein identifications using general scoring schemes.

This paper investigates the use of survival functions and expectation values to evaluate the results of protein identification experiments. These functions are standard statistical measures that can be used to reduce various protein identification scoring schemes to a common, easily interpretably representation. The relative merits of scoring systems were explored using this approach, as well as the effects of altering primary identification parameters. We would advocate the widespread use of these simple statistical measures to simplify and standardize the reporting of the confidence of protein identification results, allowing the users of different identification algorithms to compare their results in a straightforward and statistically significant manner. A method is described for measuring these distributions using information that is being discarded by most protein identification search engines, resulting in accurate survival functions that are specific to any combination of scoring algorithms, sequence databases, and mass spectra.

Mass Spectrometry↗
PubMed2004

Statistical models for protein validation using tandem mass spectral data and protein amino acid sequence databases.

The purpose of this work is to develop and verify statistical models for protein identification using peptide identifications derived from the results of tandem mass spectral database searches. Recently we have presented a probabilistic model for peptide identification that uses hypergeometric distribution to approximate fragment ion matches of database peptide sequences to experimental tandem mass spectra. Here we apply statistical models to the database search results to validate protein identifications. For this we formulate the protein identification problem in terms of two independent models, two-hypothesis binomial and multinomial models, which use the hypergeometric probabilities and cross-correlation scores, respectively. Each database search result is assumed to be a probabilistic event. The Bernoulli event has two outcomes: a protein is either identified or not. The probability of identifying a protein at each Bernoulli event is determined from relative length of the protein in the database (the null hypothesis) or the hypergeometric probability scores of the protein's peptides (the alternative hypothesis). We then calculate the binomial probability that the protein will be observed a certain number of times (number of database matches to its peptides) given the size of the data set (number of spectra) and the probability of protein identification at each Bernoulli event. The ratio of the probabilities from these two hypotheses (maximum likelihood ratio) is used as a test statistic to discriminate between true and false identifications. The significance and confidence levels of protein identifications are calculated from the model distributions. The multinomial model combines the database search results and generates an observed frequency distribution of cross-correlation scores (grouped into bins) between experimental spectra and identified amino acid sequences. The frequency distribution is used to generate p-value probabilities of each score bin. The probabilities are then normalized with respect to score bins to generate normalized probabilities of all score bins. A protein identification probability is the multinomial probability of observing the given set of peptide scores. To reduce the effect of random matches, we employ a marginalized multinomial model for small values of cross-correlation scores. We demonstrate that the combination of the two independent methods provides a useful tool for protein identification from results of database search using tandem mass spectra. A receiver operating characteristic curve demonstrates the sensitivity and accuracy level of the approach. The shortcomings of the models are related to the cases when protein assignment is based on unusual peptide fragmentation patterns that dominate over the model encoded in the peptide identification process. We have implemented the approach in a program called PROT_PROBE.

Amino Acid Sequence↗
PubMed2005

Statistical evaluation of internal and external mass calibration laws utilized in fourier transform ion cyclotron resonance mass spectrometry.

The statistical evaluation of two common and three new calibration laws utilized in Fourier transform ion cyclotron resonance mass spectrometry are presented. Electrospray ionization was used to prepare a series of mass spectra of ammonium-adducted polypropylene glycol (PPG) with an average molecular weight of 1000 Da. The singly charged PPG-1000 oligomers allowed for the description of a broad range of m/z and abundance values within each mass spectrum. The hexapole accumulation time was varied to afford a range of total ion abundance values of about an order of magnitude. To examine each of the calibration laws, we utilized cross-validation both "within-spectrum" and "between-spectra" for internally and externally calibrated data, respectively. In addition, we used t-statistics to ensure that each calibration coefficient was statistically significant and necessary to accurately describe the variation in the data. In comparison to commonly used calibration laws for internal calibration, our new calibration law based on multiple linear regression offered a 2-fold improvement in mass measurement accuracy (MMA). In comparison to external calibration laws without automatic gain control, our new calibration law using multiple regression improved the MMA by >10-fold; this improvement would increase further as the dynamic range of the measurement increases (e.g., a biological system). For both our internal and external calibration laws, the median MMA was less than 1 part-per-million. Furthermore, we investigate the number of calibrant ions as well as their required m/z range in order to successfully achieve high MMA.

Calibration↗
PubMedDate not supplied

Use of statistical and neural net approaches in predicting toxicity of chemicals.

Hierarchical quantitative structure-activity relationships (H-QSAR) have been developed as a new approach in constructing models for estimating physicochemical, biomedicinal, and toxicological properties of interest. This approach uses increasingly more complex molecular descriptors in a graduated approach to model building. In this study, statistical and neural network methods have been applied to the development of H-QSAR models for estimating the acute aquatic toxicity (LC50) of 69 benzene derivatives to Pimephales promelas (fathead minnow). Topostructural, topochemical, geometrical, and quantum chemical indices were used as the four levels of the hierarchical method. It is clear from both the statistical and neural network models that topostructural indices alone cannot adequately model this set of congeneric chemicals. Not surprisingly, topochemical indices greatly increase the predictive power of both statistical and neural network models. Quantum chemical indices also add significantly to the modeling of this set of acute aquatic toxicity data.

Animals↗
PubMed2006

Single molecule photon counting statistics for quantum mechanical chromophore dynamics.

We extend the generating function technique for calculation of single molecule photon emission statistics (Zheng, Y.; Brown, F. L. H. Phys. Rev. Lett. 2003, 90, 238305) to systems governed by multi-level quantum dynamics. This opens up the possibility to study phenomena that are outside the realm of purely stochastic and mixed quantum-stochastic models. In particular, the present methodology allows for calculation of photon statistics that are spectrally resolved and subject to quantum coherence. Several model calculations illustrate the generality of the technique and highlight quantitative and qualitative differences between quantum mechanical models and related stochastic approximations when they arise. Calculations suggest that studying photon statistics as a function of photon frequency has the potential to reveal more about system dynamics than the usual broadband detection schemes.

Color↗
PubMed2006

Fluorescence blinking statistics from CdSe core and core/shell nanorods.

We report fluorescence blinking statistics measured from single CdSe nanorods (NRs) of seven different sizes with aspect ratios ranging from 3 to 11. This study also included core/shell CdSe/ZnSe NRs and core NRs with two different surface ligands producing different degrees of surface passivation. We compare the findings for NRs to our measurements of blinking statistics from spherical CdSe core and CdSe/ZnS core/shell nanocrystals (NCs). We find that, for both NRs and spherical NCs, the off-time probability distributions are well described by a power law, while the on-time probability distributions are best described by a truncated power law, P(tau(on)) approximately tau(on)(-alpha)e((-tau)(on)/(tau)(c)). The measured crossover time, tau(c), is indistinguishable within experimental uncertainty for core and core/shell NRs, as well as for core NRs with different ligands, for the same core size, indicating that surface passivation does not affect the blinking statistics significantly. We find that, at fixed excitation intensity, 1/tau(c) increases approximately linearly with increasing NR aspect ratio; for a given sample, 1/tau(c) increases very gradually with increasing excitation intensity. Examining 1/tau(c)versus the single-particle photon absorption rate for all samples indicates that the change in NR absorption cross section with sample size can account for some but not all of the differences in crossover time. This suggests that the degree of quantum confinement may be partially responsible for the aspect ratio dependence of the crossover time.

Absorption↗
PubMed2004

Two-sample statistics for testing the equality of survival functions against improper semi-parametric accelerated failure time alternatives: an application to the analysis of a breast cancer clinical trial.

This paper presents two-sample statistics suited for testing equality of survival functions against improper semi-parametric accelerated failure time alternatives. These tests are designed for comparing either the short- or the long-term effect of a prognostic factor, or both. These statistics are obtained as partial likelihood score statistics from a time-dependent Cox model. As a consequence, the proposed tests can be very easily implemented using widely available software. A breast cancer clinical trial is presented as an example to demonstrate the utility of the proposed tests.

Breast Neoplasms↗
PubMed2004

Statistical considerations for use of composite health-related quality-of-life scores in randomized trials.

BACKGROUND: Quality of life instruments are frequently used as outcomes in randomized trials. Instruments that consist of several subscales present researchers with a choice of whether to combine some or all scales into a single composite score. There may be several clinically and scientifically reasonable alternative combinations of subscales for the primary outcome measure. MAJOR FINDINGS: The statistical efficiency of different combinations of subscales depends on the relative effect size of the intervention on each subscale and the correlation between the subscales. Simple equations can be derived for determining the relative statistical efficiency of each clinically reasonable combination of subscales. Hypothetical scenarios show that the number of patients needed in a clinical trial can be twice as great for some combinations of subscales as for others. CONCLUSIONS: There are often compelling clinical or scientific reasons to use a particular subscale or composite in a randomized trial. In the case where a number of different alternatives would be reasonable, statistical efficiency can help guide the choice of endpoint.

Data Interpretation, Statistical↗