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Behavior Research Methods Jun 2022Growth mixture modeling is a common tool for longitudinal data analysis. One of the key assumptions of traditional growth mixture modeling is that repeated measures...
Growth mixture modeling is a common tool for longitudinal data analysis. One of the key assumptions of traditional growth mixture modeling is that repeated measures within each class are normally distributed. When this normality assumption is violated, traditional growth mixture modeling may provide misleading model estimation results and suffer from nonconvergence. In this article, we propose a robust approach to growth mixture modeling based on conditional medians and use Bayesian methods for model estimation and inferences. A simulation study is conducted to evaluate the performance of this approach. It is found that the new approach has a higher convergence rate and less biased parameter estimation than the traditional growth mixture modeling approach when data are skewed or have outliers. An empirical data analysis is also provided to illustrate how the proposed method can be applied in practice.
Topics: Bayes Theorem; Computer Simulation; Humans; Models, Statistical; Research Design
PubMed: 34590287
DOI: 10.3758/s13428-021-01655-w -
Bulletin of Mathematical Biology Apr 2016The genome median problem is an important problem in phylogenetic reconstruction under rearrangement models. It can be stated as follows: Given three genomes, find a...
The genome median problem is an important problem in phylogenetic reconstruction under rearrangement models. It can be stated as follows: Given three genomes, find a fourth that minimizes the sum of the pairwise rearrangement distances between it and the three input genomes. In this paper, we model genomes as matrices and study the matrix median problem using the rank distance. It is known that, for any metric distance, at least one of the corners is a [Formula: see text]-approximation of the median. Our results allow us to compute up to three additional matrix median candidates, all of them with approximation ratios at least as good as the best corner, when the input matrices come from genomes. We also show a class of instances where our candidates are optimal. From the application point of view, it is usually more interesting to locate medians farther from the corners, and therefore, these new candidates are potentially more useful. In addition to the approximation algorithm, we suggest a heuristic to get a genome from an arbitrary square matrix. This is useful to translate the results of our median approximation algorithm back to genomes, and it has good results in our tests. To assess the relevance of our approach in the biological context, we ran simulated evolution tests and compared our solutions to those of an exact DCJ median solver. The results show that our method is capable of producing very good candidates.
Topics: Algorithms; Computer Simulation; Evolution, Molecular; Genome; Mathematical Concepts; Models, Genetic; Models, Statistical; Phylogeny
PubMed: 27072561
DOI: 10.1007/s11538-016-0162-4 -
Health Economics May 2021Comparing median outcomes to gauge treatment effectiveness is widespread practice in clinical and other investigations. While common, such difference-in-median...
Comparing median outcomes to gauge treatment effectiveness is widespread practice in clinical and other investigations. While common, such difference-in-median characterizations of effectiveness are but one way to summarize how outcome distributions compare. This paper explores properties of median treatment effects (TEs) as indicators of treatment effectiveness. The paper's main focus is on decisionmaking based on median TEs and it proceeds by considering two paths a decisionmaker might follow. Along one, decisions are based on point-identified differences in medians alongside partially identified median differences; along the other decisions are based on point-identified differences in medians in conjunction with other point-identified parameters. On both paths familiar difference-in-median measures play some role yet in both the traditional standards are augmented with information that will often be relevant in assessing treatments' effectiveness. Implementing either approach is straightforward. In addition to its analytical results the paper considers several policy contexts in which such considerations arise. While the paper is framed by recently reported findings on treatments for COVID-19 and uses several such studies to explore empirically some properties of median-treatment-effect measures of effectiveness, its results should be broadly applicable.
Topics: COVID-19; Clinical Trials as Topic; Decision Making; Humans; Treatment Outcome
PubMed: 33667329
DOI: 10.1002/hec.4233 -
IEEE Transactions on Image Processing :... Mar 2016Local binary patterns (LBP) are considered among the most computationally efficient high-performance texture features. However, the LBP method is very sensitive to image...
Local binary patterns (LBP) are considered among the most computationally efficient high-performance texture features. However, the LBP method is very sensitive to image noise and is unable to capture macrostructure information. To best address these disadvantages, in this paper, we introduce a novel descriptor for texture classification, the median robust extended LBP (MRELBP). Different from the traditional LBP and many LBP variants, MRELBP compares regional image medians rather than raw image intensities. A multiscale LBP type descriptor is computed by efficiently comparing image medians over a novel sampling scheme, which can capture both microstructure and macrostructure texture information. A comprehensive evaluation on benchmark data sets reveals MRELBP's high performance-robust to gray scale variations, rotation changes and noise-but at a low computational cost. MRELBP produces the best classification scores of 99.82%, 99.38%, and 99.77% on three popular Outex test suites. More importantly, MRELBP is shown to be highly robust to image noise, including Gaussian noise, Gaussian blur, salt-and-pepper noise, and random pixel corruption.
PubMed: 26829791
DOI: 10.1109/TIP.2016.2522378 -
BMC Medical Research Methodology Feb 2012The results of Randomized Controlled Trials (RCTs) on time-to-event outcomes that are usually reported are median time to events and Cox Hazard Ratio. These do not...
BACKGROUND
The results of Randomized Controlled Trials (RCTs) on time-to-event outcomes that are usually reported are median time to events and Cox Hazard Ratio. These do not constitute the sufficient statistics required for meta-analysis or cost-effectiveness analysis, and their use in secondary analyses requires strong assumptions that may not have been adequately tested. In order to enhance the quality of secondary data analyses, we propose a method which derives from the published Kaplan Meier survival curves a close approximation to the original individual patient time-to-event data from which they were generated.
METHODS
We develop an algorithm that maps from digitised curves back to KM data by finding numerical solutions to the inverted KM equations, using where available information on number of events and numbers at risk. The reproducibility and accuracy of survival probabilities, median survival times and hazard ratios based on reconstructed KM data was assessed by comparing published statistics (survival probabilities, medians and hazard ratios) with statistics based on repeated reconstructions by multiple observers.
RESULTS
The validation exercise established there was no material systematic error and that there was a high degree of reproducibility for all statistics. Accuracy was excellent for survival probabilities and medians, for hazard ratios reasonable accuracy can only be obtained if at least numbers at risk or total number of events are reported.
CONCLUSION
The algorithm is a reliable tool for meta-analysis and cost-effectiveness analyses of RCTs reporting time-to-event data. It is recommended that all RCTs should report information on numbers at risk and total number of events alongside KM curves.
Topics: Algorithms; Data Interpretation, Statistical; Humans; Kaplan-Meier Estimate; Meta-Analysis as Topic; Observer Variation; Proportional Hazards Models; Randomized Controlled Trials as Topic; Reproducibility of Results; Research Design; Survival Analysis
PubMed: 22297116
DOI: 10.1186/1471-2288-12-9 -
Clinica Chimica Acta; International... Jun 2015In spite of the well-established external quality assessment and proficiency testing surveys of analytical quality performance in laboratory medicine, a simple tool to...
BACKGROUND
In spite of the well-established external quality assessment and proficiency testing surveys of analytical quality performance in laboratory medicine, a simple tool to monitor the long-term analytical stability as a supplement to the internal control procedures is often needed.
METHOD
Patient data from daily internal control schemes was used for monthly appraisal of the analytical stability. This was accomplished by using the monthly medians of patient results to disclose deviations from analytical stability, and by comparing divergences with the quality specifications for allowable analytical bias based on biological variation.
RESULTS
Seventy five percent of the twenty analytes achieved on two COBASs INTEGRA 800 instruments performed in accordance with the optimum and with the desirable specifications for bias.
DISCUSSION
Patient results applied in analytical quality performance control procedures are the most reliable sources of material as they represent the genuine substance of the measurements and therefore circumvent the problems associated with non-commutable materials in external assessment.
CONCLUSION
Patient medians in the monthly monitoring of analytical stability in laboratory medicine are an inexpensive, simple and reliable tool to monitor the steadiness of the analytical practice.
Topics: Automation, Laboratory; Bilirubin; Blood Proteins; Chemistry Techniques, Analytical; Cholesterol; Hematology; Humans; Iron; Laboratories; Magnesium; Potassium; Quality Control; Reproducibility of Results; Sodium; Triglycerides
PubMed: 25920692
DOI: 10.1016/j.cca.2015.04.024 -
BMC Bioinformatics May 2018Recently, Pereira Zanetti, Biller and Meidanis have proposed a new definition of a rearrangement distance between genomes. In this formulation, each genome is...
BACKGROUND
Recently, Pereira Zanetti, Biller and Meidanis have proposed a new definition of a rearrangement distance between genomes. In this formulation, each genome is represented as a matrix, and the distance d is the rank distance between these matrices. Although defined in terms of matrices, the rank distance is equal to the minimum total weight of a series of weighted operations that leads from one genome to the other, including inversions, translocations, transpositions, and others. The computational complexity of the median-of-three problem according to this distance is currently unknown. The genome matrices are a special kind of permutation matrices, which we study in this paper. In their paper, the authors provide an [Formula: see text] algorithm for determining three candidate medians, prove the tight approximation ratio [Formula: see text], and provide a sufficient condition for their candidates to be true medians. They also conduct some experiments that suggest that their method is accurate on simulated and real data.
RESULTS
In this paper, we extend their results and provide the following: Three invariants characterizing the problem of finding the median of 3 matrices A sufficient condition for uniqueness of medians that can be checked in O(n) A faster, [Formula: see text] algorithm for determining the median under this condition A new heuristic algorithm for this problem based on compressed sensing A [Formula: see text] algorithm that exactly solves the problem when the inputs are orthogonal matrices, a class that includes both permutations and genomes as special cases.
CONCLUSIONS
Our work provides the first proof that, with respect to the rank distance, the problem of finding the median of 3 genomes, as well as the median of 3 permutations, is exactly solvable in polynomial time, a result which should be contrasted with its NP-hardness for the DCJ (double cut-and-join) distance and most other families of genome rearrangement operations. This result, backed by our experimental tests, indicates that the rank distance is a viable alternative to the DCJ distance widely used in genome comparisons.
Topics: Algorithms; Computer Simulation; Databases, Genetic; Gene Rearrangement; Genome; Genomics; Models, Genetic; Mutation
PubMed: 29745865
DOI: 10.1186/s12859-018-2131-4 -
Computer Methods and Programs in... Nov 2014Techniques for conducting hypothesis testing on the median and other quantiles of two or more subgroups under complex survey design are limited. In this paper, we...
Techniques for conducting hypothesis testing on the median and other quantiles of two or more subgroups under complex survey design are limited. In this paper, we introduce programs in both SAS and R to perform such a test. A detailed illustration of the computations, macro variable definitions, input and output for the SAS and R programs are also included in the text. Urinary iodine data from National Health and Nutrition Examination Survey (NHANES) are used as examples for comparing medians between females and males as well as comparing the 75th percentiles among three salt consumption groups.
Topics: Algorithms; Computer Simulation; Data Interpretation, Statistical; Female; Humans; Male; Models, Statistical; Nutrition Surveys; Programming Languages; Software
PubMed: 25123100
DOI: 10.1016/j.cmpb.2014.07.007 -
American Journal of Preventive Medicine Aug 2011Recent epidemiologic evidence points to the health risks of prolonged sitting, that are independent of physical activity, but few papers have reported the descriptive...
BACKGROUND
Recent epidemiologic evidence points to the health risks of prolonged sitting, that are independent of physical activity, but few papers have reported the descriptive epidemiology of sitting in population studies with adults.
PURPOSE
This paper reports the prevalence of "high sitting time" and its correlates in an international study in 20 countries.
METHODS
Representative population samples from 20 countries were collected 2002-2004, and a question was asked on usual weekday hours spent sitting. This question was part of the International Prevalence Study, using the International Physical Activity Questionnaire (IPAQ). The sitting measure has acceptable reliability and validity. Daily sitting time was compared among countries, and by age group, gender, educational attainment, and physical activity.
RESULTS
Data were available for 49,493 adults aged 18-65 years from 20 countries. The median reported sitting time was 300 minutes/day, with an interquartile range of 180-480 minutes. Countries reporting the lowest amount of sitting included Portugal, Brazil, and Colombia (medians ≤180 min/day), whereas adults in Taiwan, Norway, Hong Kong, Saudi Arabia, and Japan reported the highest sitting times (medians ≥360 min/day). In adjusted analyses, adults aged 40-65 years were significantly less likely to be in the highest quintile for sitting than adults aged 18-39 years (AOR=0.796), and those with postschool education had higher sitting times compared with those with high school or less education (OR=1.349). Physical activity showed an inverse relationship, with those reporting low activity on the IPAQ three times more likely to be in the highest-sitting quintile compared to those reporting high physical activity.
CONCLUSIONS
Median sitting time varied widely across countries. Assessing sitting time is an important new area for preventive medicine, in addition to assessing physical activity and sedentary behaviors. Population surveys that monitor lifestyle behaviors should add measures of sitting time to physical activity surveillance. Moreover, the use of objective measures to capture the spectrum of sedentary (sitting) and physical activity behaviors is encouraged, particularly in low- and middle-income countries commencing new surveillance activities.
Topics: Adolescent; Adult; Age Factors; Aged; Cross-Cultural Comparison; Educational Status; Epidemiologic Methods; Female; Health Behavior; Humans; Male; Middle Aged; Motor Activity; Population Surveillance; Reproducibility of Results; Sedentary Behavior; Surveys and Questionnaires; Time Factors; Young Adult
PubMed: 21767731
DOI: 10.1016/j.amepre.2011.05.003 -
Clinica Chimica Acta; International... Jul 2011Statistical process control is foundational in laboratory medicine. It typically uses artificial control specimens and can detect some, but not all, analytical defects....
BACKGROUND
Statistical process control is foundational in laboratory medicine. It typically uses artificial control specimens and can detect some, but not all, analytical defects. A practical, robust method to more directly detect trends in patient results, such as monitoring mean or median patient results, is desirable.
METHODS
We generated a simulated set of laboratory results from a normal distribution, and also downloaded sequential patient results for serum sodium and CA 19-9. For each of the three data sets we calculated the standard error of the mean and estimated the standard error of the median by bootstrapping.
RESULTS
The standard error of the mean is a practical, easily calculated summary statistic that can be used to construct control charts. The standard error of the median, cannot be reliably estimated without using bootstrap methods, but is more resistant to outliers. Our study confirms a simple relationship between the variance of the median and the variance of the mean, i.e., for Gaussian distributions, Var[Median]/Var[Mean]=π/2. We also confirm that for skewed distributions, the median is more stable than the mean, implying Var[Median]/Var[Mean]<1. Finally, we establish a sample size of 200 individual patient results as sufficient for monitoring medians for data from approximately Gaussian distributions.
CONCLUSIONS
Monitoring patient result medians represents a practical, statistically self-consistent approach to laboratory quality control.
Topics: Clinical Laboratory Techniques; Humans; Quality Control; Reproducibility of Results; Sensitivity and Specificity
PubMed: 21549689
DOI: 10.1016/j.cca.2011.04.024