Evidence map›Paper›PMID 25558154›Full record

ReviewAyu2014

Some basic aspects of statistical methods and sample size determination in health science research.

V S Binu, Shreemathi S Mayya, Murali Dhar

Abstract readReview
In one paragraph

Review in Ayu, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed.

  1. Article
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  14. Statistical methods and common problems in medical or biomedical science research.International journal of physiology, pathophysiology and pharmacology · 2017
    Review
  15. Article
  16. Basic statistical tools in research and data analysis.Indian journal of anaesthesia · 2016
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

V S BinuDepartment of Statistics, Manipal University, Manipal, Karnataka, India.
Shreemathi S MayyaDepartment of Statistics, Manipal University, Manipal, Karnataka, India.
Murali DharDepartment of Population Policies and Programmes, International Institute for Population Sciences, Deonar, Mumbai, Maharashtra, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A health science researcher may sometimes wonder "why statistical methods are so important in research?" Simple answer is that, statistical methods are used throughout a study that includes planning, designing, collecting data, analyzing and drawing meaningful interpretation and report the findings. Hence, it is important that a researcher knows the concepts of at least basic statistical methods used at various stages of a research study. This helps the researcher in the conduct of an appropriately well-designed study leading to valid and reliable results that can be generalized to the population. A well-designed study possesses fewer biases, which intern gives precise, valid and reliable results. There are many statistical methods and tests that are used at various stages of a research. In this communication, we discuss the overall importance of statistical considerations in medical research with the main emphasis on estimating minimum sample size for different study objectives.

Indexed as

Applicationshealth-sciences-researchsample-sizestatistics

Identifiers

PMID25558154
PMCPMC4279315

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.