{"doi":"10.1002/jrsm.1626","title":"<scp>RIMeta</scp>: An R shiny tool for estimating the reference interval from a meta‐analysis","abstract":"A reference interval, or an interval in which a prespecified proportion of measurements from a healthy population are expected to fall, is used to determine whether a person's measurement is typical of a healthy individual. For a specific biomarker, multiple published studies may provide data collected from healthy participants. A reference interval estimated by combining the data across these studies is typically more generalizable than a reference interval based on a single study. Methods for estimating reference intervals from random effects meta-analysis and fixed-effects meta-analysis have been recently proposed and implemented using R software. We present an R Shiny tool, RIMeta, implementing these methods, which allows users not proficient in R to estimate a reference interval from a meta-analysis using aggregate data (mean, standard deviation, and sample size) from each study. RIMeta (https://cers.shinyapps.io/RIMeta/) provides users a convenient way to estimate a reference interval from a meta-analysis and to generate the reference interval plot to visualize the results. The use of this web-based R Shiny tool does not require the installation of R or any background knowledge of programming. We explain all functions of the R Shiny tool and illustrate how to use it with a real data example.","journal":"Research Synthesis Methods","year":2023,"id":360144,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":9,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9302,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2023-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":368392,"name":"Wenhao Cao","orcid":"0000-0001-9213-3705","position":1,"is_corresponding":false},{"id":49892,"name":"Haitao Chu","orcid":"0000-0003-0932-598X","position":2,"is_corresponding":false},{"id":272300,"name":"Fateh Bazerbachi","orcid":"0000-0003-4599-2042","position":3,"is_corresponding":false},{"id":557937,"name":"Lianne Siegel","orcid":"0000-0001-9440-9146","position":4,"is_corresponding":false},{"id":1111555,"name":"Ziren Jiang","orcid":"0000-0002-5830-327X","position":0,"is_corresponding":true}],"reference_count":31,"raw_metadata":null,"created_at":"2026-07-19T01:14:01.896928Z","pmid":"36725922","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}