Identifying and removing duplicate records from systematic review searches

Related Experiment Video

Updated: Mar 31, 2026

Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases
05:02

Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases

Published on: October 24, 2019

34.4K

Yoojin Kwon, Michelle Lemieux, Jill McTavish

    Journal of the Medical Library Association : JMLA
    |October 30, 2015
    PubMed
    Abstract

    Keywords:
    Biomedical ResearchStandards, Duplicate Publication as Topic, PublicationsStandards, Review Literature as Topic

    More Related Videos

    Meta-analysis of Voxel-Based Neuroimaging Studies using Seed-based d Mapping with Permutation of Subject Images SDM-PSI06:26

    Meta-analysis of Voxel-Based Neuroimaging Studies using Seed-based d Mapping with Permutation of Subject Images SDM-PSI

    Published on: November 27, 2019

    79.2K
    Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index06:55

    Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

    Published on: January 8, 2020

    15.5K

    Related Concept Videos

    Systematic Error: Methodological and Sampling Errors01:15

    Systematic Error: Methodological and Sampling Errors

    In the case of systematic errors, the sources can be identified, and the errors can be subsequently minimized by addressing these sources. According to the source, systematic errors can be divided into sampling, instrumental, methodological, and personal errors.
    Sampling errors originate from improper sampling methods or the wrong sample population. These errors can be minimized by refining the sampling strategy. Defective instruments or faulty calibrations are the sources of instrumental...
    11.4K
    Systematic Sampling Method01:17

    Systematic Sampling Method

    Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
    Systematic sampling is one of the simplest methods...
    13.9K
    Comparing Copy Number Variations and SNPs02:26

    Comparing Copy Number Variations and SNPs

    Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
    Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...
    19.3K
    Blind Procedures02:07

    Blind Procedures

    Ideally, the people who observe and record the children’s behavior are unaware of who was assigned to the experimental or control group, in order to control for experimenter bias. Experimenter bias refers to the possibility that a researcher’s expectations might skew the results of the study. Remember, conducting an experiment requires a lot of planning, and the people involved in the research project have a vested interest in supporting their hypotheses. If the observers knew which...
    13.9K
    Chi-square Analysis02:46

    Chi-square Analysis

    The chi-square test is a statistical hypothesis test. It is used to check whether there is a significant difference between an expected value and an observed value. In the context of genetics, it enables us to either accept or reject a hypothesis, based on how much the observed values deviate from the expected values.
    The chi-square test was developed by Pearson in 1990.
    The first step of performing a Chi-square analysis is to establish a null hypothesis, which assumes that there is no real...
    44.7K
    Strategies for Assessing and Addressing Confounding01:25

    Strategies for Assessing and Addressing Confounding

    Confounding is a critical issue in epidemiological studies, often leading to misleading conclusions about associations between exposures and outcomes. It occurs when the relationship between the exposure and the outcome is mixed with the effects of other factors that influence the outcome. Given that, addressing confounding is of high importance for drawing accurate inferences in research.
    Confounding can be addressed at both the design phase of a study and through analytical methods after data...
    532