Evidence map›Paper›PMID 15840177›Full record

ArticleBMC medical research methodology2005

Estimating the mean and variance from the median, range, and the size of a sample.

Stela Pudar Hozo, Benjamin Djulbegovic, Iztok Hozo

4 registry-linked trialsAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC medical research methodology, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 4 registered trials, which are not on this map. Cited by 4,129 papers, 110 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4,129citing papers in PubMed, 110 pooled it
–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.

NCT03470415 unknown statusnot on this mapstarted 2018, after this paper: background citation

Relation of Epicardial Fat and Diabetic Nephropathy in Egyptian Patients

Typeobservational_patient_registrySponsorAssiut UniversityRan2018 to 2019Enrolled100ConditionsType2 Diabetes Mellitus
NCT03657667 nacompletednot on this mapstarted 2018, after this paper: background citation

Evaluation of Pain Before and After Removal of Non-obstructive Kidney Stones

TypeinterventionalSponsorCentre hospitalier de l'Université de Montréal (CHUM)Ran2018 to 2023Enrolled43ConditionsKidney StoneArmsUreteroscopy
NCT04517396 phase2completednot on this mapstarted 2020, after this paper: background citation

FEnofibRate as a Metabolic INtervention for Coronavirus Disease 2019

TypeinterventionalSponsorUniversity of PennsylvaniaRan2020 to 2022Enrolled701ConditionsCovid19ArmsFenofibrate/fenofibric acid, Placebo, Usual care
NCT05224089 phase4recruitingnot on this mapstarted 2022, after this paper: background citation

Bilateral Mid-Abdominal Transverse Abdominis Plane and Rectus Sheath Blocks Comparing The Use of Liposomal Bupivacaine/Bupivacaine vs. Regular Bupivacaine in Laparoscopic Colectomy Procedures.

TypeinterventionalSponsorHartford HospitalRan2022 to 2026Enrolled114ConditionsBowel DiseaseArmsLiposomal Bupivicaine/Bupivacaine Admixture, Bupivacaine HCL
3 · Its place in the literature

Who cites it

4,129 citing papers in PubMed, 110 syntheses or guidelines pooled it.

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4,069 more citing papers are in PubMed but not listed here.

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.

Stela Pudar HozoDepartment of Mathematics, Indiana University Northwest, Gary, IN 46408, USA. spudar@iun.edu
Benjamin Djulbegovic
Iztok Hozo

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundUsually the researchers performing meta-analysis of continuous outcomes from clinical trials need their mean value and the variance (or standard deviation) in order to pool data. However, sometimes the published reports of clinical trials only report the median, range and the size of the trial.

methodsIn this article we use simple and elementary inequalities and approximations in order to estimate the mean and the variance for such trials. Our estimation is distribution-free, i.e., it makes no assumption on the distribution of the underlying data.

resultsWe found two simple formulas that estimate the mean using the values of the median (m), low and high end of the range (a and b, respectively), and n (the sample size). Using simulations, we show that median can be used to estimate mean when the sample size is larger than 25. For smaller samples our new formula, devised in this paper, should be used. We also estimated the variance of an unknown sample using the median, low and high end of the range, and the sample size. Our estimate is performing as the best estimate in our simulations for very small samples (n < or = 15). For moderately sized samples (15 < n < or = 70), our simulations show that the formula range/4 is the best estimator for the standard deviation (variance). For large samples (n > 70), the formula range/6 gives the best estimator for the standard deviation (variance). We also include an illustrative example of the potential value of our method using reports from the Cochrane review on the role of erythropoietin in anemia due to malignancy.

conclusionUsing these formulas, we hope to help meta-analysts use clinical trials in their analysis even when not all of the information is available and/or reported.

Indexed as

Analysis of VarianceMeta-Analysis as TopicSample SizeClinical Trials as TopicComputer SimulationHumansModels, Statistical

Identifiers

PMID15840177
PMCPMC1097734

What OpenQuestion holds

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Registered trials

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.