scholarly journals Statistical methods for the analyses in clinical practice. Part 1. Univariate statistical analysis

2009 ◽  
Vol 55 (5) ◽  
pp. 48-55 ◽  
Author(s):  
P O Rumyantsev ◽  
U V Saenko ◽  
U V Rumyantseva
Keyword(s):  
Clinical Practice ◽  
Statistical Analysis ◽  
Clinical Study ◽  
Medical Research ◽  
Statistical Methods ◽  
Multivariate Statistics ◽  
Statistical Treatment ◽  
Descriptive Statistics ◽  
Integral Component ◽  
Mathematical Computation

Statistical analysis is an integral component of any clinical study. The objective of the present work was to assist clinicians in understanding various methods of statistical treatment of medical findings without going into details of mathematical computation. The most strongly sought for and popular analytical procedures are considered in application to clinical and experimental medical research. Part 1 of this communication is focused on descriptive statistics and methods of univariate statistical analysis. Part II will be concerned with the analysis of survivorship and multivariate statistics.

Latency models: the statistical analysis of response times

1982 ◽  
Vol 12 (3) ◽  
pp. 659-665 ◽  
Author(s):  
Graham Dunn ◽  
Din Master
Keyword(s):  
Statistical Analysis ◽  
Statistical Methods ◽  
Linear Models ◽  
Response Times ◽  
Descriptive Statistics ◽  
Failure Times ◽  
Log Linear

SYNOPSISThis paper introduces statistical methods suitable for the analysis of response, survival or failure times and, in particular, latencies measured in experiments on the speed of recall of memories. The discussion includes the use of simple descriptive statistics, as well as an explanation of the role of linear-logistic and log-linear models.

A Clinical study to evaluate the role of Kharjooradi Mantha in the enhancement of Ojo Guna in Madatyayi subjects

2018 ◽  
Vol 3 (5) ◽  
Author(s):  
Dr. Aqeeb Javeed ◽  
Dr. Vasudev Chate ◽  
Dr. Shreevathsa .
Keyword(s):  
Statistical Analysis ◽  
Clinical Study ◽  
Clinical Efficacy ◽  
Random Sampling ◽  
Sampling Method ◽  
Simple Random Sampling ◽  
Descriptive Statistics ◽  
Spss Software

A study was conducted to access clinical efficacy of ‘Kharjooradi Mantha in the enhancement of Ojo Guna in the subjects of Madatyaya. As Madhya has 10 Gunas which are exactly opposite to the 10 Gunas of Ojas. 35 patients of Madatyaya were selected by simple random sampling method. Kharjooradi Mantha was given in two divided doses once in the morning and evening after food with Jala as Anupana for duration of 28 days. Gradation scale was used depending upon their severity to assess the effect of the treatment objectively and to monitor the disease; however at the time of statistical analysis the outcome was statistically analyzed i.e. before treatment and after treatment by using Descriptive Statistics, Chi squares test and Cramer’s V by using windows SPSS Software. It was revealed that Kharjooradi Mantha was effective in the enhancement of Ojo Guna in the subjects of Madatyayia. It significantly reduced the symptoms such as Chardi, Aruchi, Hrullasa, Tandra, Staimitya, Gaurava, Hikka, Svasa, Kasa, Pralapa, Sirakampa, Parashvashola, Nidranasha, Trsna, Daha, Dourbalya, Murcha and Sweda. Kharjooradi Mantha did the Tarpana, Agnideepana and Anulomana there by increasing the Ojo Gunas.

Oxford Handbook of Medical Statistics

2020 ◽  
Author(s):  
Janet L. Peacock ◽  
Phil J. Peacock
Keyword(s):  
Clinical Practice ◽  
Medical Students ◽  
Medical Research ◽  
Sample Size ◽  
Statistical Methods ◽  
Medical Statistics ◽  
Wide Range ◽  
Chi Squared ◽  
Published Research ◽  
Difficult Subject

A good understanding of medical statistics is essential to evaluate medical research and to choose appropriate ways of implementing findings in clinical practice. The Oxford Handbook of Medical Statistics, second edition, has been written to provide doctors and medical students with a comprehensive yet concise account of this often difficult subject. Described by readers as a ‘statistical Bible’, this new edition maintains the accessibility and thoroughness of the original, and includes comprehensive updates including new sections on transitional medicine, cluster designs, and modern statistical packages. The handbook promotes understanding and interpretation of statistical methods across a wide range of topics, from study design and sample size considerations, through t and chi-squared tests, to complex multifactorial analyses, all using examples from published research. References and further reading are included, to allow deeper understanding on specific topics. Featuring a new chapter on how to use this book in different medical contexts, the Oxford Handbook of Medical Statistics helps readers to conduct their own research and critically appraise others' work.

Statistical methods in medicine: basic knowledge for the internist

2020 ◽  
pp. 28-33
Author(s):  
A. Krylov
Keyword(s):  
Statistical Analysis ◽  
Data Processing ◽  
Medical Research ◽  
Statistical Methods ◽  
Basic Knowledge ◽  
Research Involvement

The article describes methods of statistical analysis that a physician needs to know in order to conduct medical research. Involvement of internists in training and use of statistical methods of processing and planning will improve their orientation in a variety of existing statistical methods of data processing, as well as will help to understand the importance and relevance of using statistics in medical research in order to create competent, personalized approaches to a patient.

scholarly journals Statistical methods for the analyses in clinical practice. Part 2. Survival analysis and multivariate statistics

2009 ◽  
Vol 55 (6) ◽  
pp. 48-56 ◽  
Author(s):  
P O Rumyantsev ◽  
V A Saenko ◽  
Ul'yana Viktorovna Rumyantseva ◽  
Sergey Yur'evich Chekin
Keyword(s):  
Survival Analysis ◽  
Statistical Analysis ◽  
Univariate Analysis ◽  
Statistical Treatment ◽  
Descriptive Statistics ◽  
Experimental Medicine ◽  
Multivariate Methods ◽  
Practical Application ◽  
Basic Principles ◽  
Insight Into

Statistical analysis is an integral component of clinical studies. The objective of the present paper is to assist clinicians in getting deeper insight into basic principles underlying different methods available for the statistical treatment of medical data without a detailed description of relevant mathematical calculations. The most popular and widely used methods of statistical analysis are considered with special reference to their practical application in clinical and experimental medicine. Part I of the review was devoted to foundations of descriptive statistics and univariate analysis. Part II is focused on the principles of survival analysis and multivariate methods.

An approach to the clinical manifestation of Rupavriddhi Rupahani Rupantara in Avarana

2018 ◽  
Vol 3 (4) ◽  
Author(s):  
Dr. Sharanamma . ◽  
Dr. A. S. Prashanth ◽  
Dr. S. G. Chavan
Keyword(s):  
Clinical Practice ◽  
Clinical Study ◽  
Present Article ◽  
Clinical Manifestation ◽  
Basic Concept ◽  
Favorable Condition ◽  
Wrong Diagnosis

Ayurveda believes in different pathology which sets in different Srotas to produce different diseases. Whenever a favorable condition and situation arise, diseases will manifest. Nanatmaja Vikara, Anubandha, Gatavata and Avarana are different pathologies explained in Ayurveda. Avarana is one of the most difficult concept to understand teach and incorporate in clinical practice. It is either least observed, diagnosed or goes unidentified due to lack of skill. To understand and analyze the Avarana, Meticulous knowledge of basic concept of Ayurveda is essential. It is assumed that symptoms complex in Avarana leads to misunderstanding, wrong diagnosis and sometimes end with complications. The symptoms produced in Avarana are based on the principles of Rupahani (Karmakshaya), Rupavriddi (Karmavriddhi) and Rupantara (Anya Karma). The present article is an attempt made to have a critical clinical study of role of Avarana in the manifestation of Rupavriddhi, Rupahani, Rupantara.

scholarly journals Variability of Prognostic Results Based on Biological Parameters in Sickle Cell Disease Cohort Studies in Children: What Should Clinicians Know?

Children ◽  
2021 ◽  
Vol 8 (2) ◽  
pp. 143
Author(s):  
Julie Sommet ◽  
Enora Le Roux ◽  
Bérengère Koehl ◽  
Zinedine Haouari ◽  
Damir Mohamed ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Sickle Cell Disease ◽  
Cohort Studies ◽  
Statistical Methods ◽  
Sickle Cell ◽  
Biological Parameters ◽  
Analysis Method ◽  
Cell Disease ◽  
Statistical Analysis Method

Background: Many pediatric studies describe the association between biological parameters (BP) and severity of sickle cell disease (SCD) using different methods to collect or to analyze BP. This article assesses the methods used for collection and subsequent statistical analysis of BP, and how these impact prognostic results in SCD children cohort studies. Methods: Firstly, we identified the collection and statistical methods used in published SCD cohort studies. Secondly, these methods were applied to our cohort of 375 SCD children, to evaluate the association of BP with cerebral vasculopathy (CV). Results: In 16 cohort studies, BP were collected either once or several times during follow-up. The identified methods in the statistical analysis were: (1) one baseline value per patient (2) last known value; (3) mean of all values; (4) modelling of all values in a two-stage approach. Applying these four different statistical methods to our cohort, the results and interpretation of the association between BP and CV were different depending on the method used. Conclusion: The BP prognostic value depends on the chosen statistical analysis method. Appropriate statistical analyses of prognostic factors in cohort studies should be considered and should enable valuable and reproducible conclusions.

Evaluation software for effects produced by MOOC in mediums with different linguistically levels

2018 ◽  
Vol 34 (3) ◽  
pp. 633-645
Author(s):  
Cornel Samoilă ◽  
Doru Ursuţiu ◽  
Vlad Jinga
Keyword(s):  
Statistical Analysis ◽  
Statistical Methods ◽  
Rapid Assessment ◽  
Assessment Method ◽  
Behavioral Changes ◽  
Strong Negation ◽  
Face To Face ◽  
Made In ◽  
The Way

Abstract MOOC appearance has produced, in a first phase, more discussions than contributions. Despite pessimistic opinions or those catastrophic foreseeing the end of the classic education by accepting MOOC, the authors consider that, as it is happening in all situations when a field is reformed, instead of criticism or catastrophic predictions, an assessment should be simply made. MOOC will not be better or worse if it is discussed and dissected but can be tested in action, perfected by results, or abandoned if it has no prospects. Without testing, no decision is valid. A similarity between the MOOC appearance and the appearance of the idea of flying machines heavier than air can be made. In the flight case, the first reaction was a strong negation (including at Academies level) and only performing the first independent flight with an apparatus heavier than air has shifted orientation from denial to contributions. So, practical tests clarified the battle between ideas. The authors of this article encourage the idea of testing–assessment and, therefore, imagined and proposed one software for quickly assess whether MOOC produces changes in knowledge, by simply transferring courses from ‘face-to-face’ environment into the virtual one. Among the methods of statistical analysis for student behavioral changes was chosen the Keppel method. It underpins the assessment method of this work being approached using both the version with one variable and also with three variables. It is intended that this attempts to pave the way for other series of rapid assessment regarding MOOC effects (using other statistical methods). We believe, that this is the only approach that can lead either to improve the system or to renunciation.

scholarly journals After placebo: In medical research and clinical practice R.Nunn, ArjanaMedia 2015

2018 ◽  
Vol 24 (5) ◽  
pp. 1265-1267
Author(s):  
Cosima Locher ◽  
Jens Gaab ◽  
Michael Loughlin ◽  
Charlotte Blease
Keyword(s):  
Clinical Practice ◽  
Medical Research

Recent and Planned Developments of the Program OxCal

Radiocarbon ◽  
2013 ◽  
Vol 55 (2) ◽  
pp. 720-730 ◽  
Author(s):  
Christopher Bronk Ramsey ◽  
Sharen Lee
Keyword(s):  
Statistical Analysis ◽  
Statistical Methods ◽  
Software Package ◽  
Model Averaging ◽  
Data Sets ◽  
Radiocarbon Dates ◽  
New Approach ◽  
New Models ◽  
Multiphase Models ◽  
Deposition Models

OxCal is a widely used software package for the calibration of radiocarbon dates and the statistical analysis of 14C and other chronological information. The program aims to make statistical methods easily available to researchers and students working in a range of different disciplines. This paper will look at the recent and planned developments of the package. The recent additions to the statistical methods are primarily aimed at providing more robust models, in particular through model averaging for deposition models and through different multiphase models. The paper will look at how these new models have been implemented and explore the implications for researchers who might benefit from their use. In addition, a new approach to the evaluation of marine reservoir offsets will be presented. As the quantity and complexity of chronological data increase, it is also important to have efficient methods for the visualization of such extensive data sets and methods for the presentation of spatial and geographical data embedded within planned future versions of OxCal will also be discussed.

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