GCRI · Labs
Protokol penelitian
A research protocol fixes, before data are collected, what a study asks, how it will answer and what would count as an answer: the hypotheses, the design, the controls, the outcomes, the sample and the analysis. Many failures of credibility trace back to a protocol that was vague, unwritten or changed after the data were seen. This page sets out how protocols are built, registered, reviewed and reported, and what ethics committees, editors and funders rely on when they accept a study’s claims.
Bagaimana pekerjaan berjalan.
Papan protokol dan replikasi
Research protocols · Labs · Quarter 3
Protokol
| PR-378 sensor drift | Eksperimen lapangan | Ya | Disetujui | Berjalan |
| PR-705 AI triage | Diacak | Ya | Kondisi | Penyiapan |
| PR-694 message recall | Eksperimen survei | Ya | Disetujui | Selesai |
| PR-360 heat exposure | Kohort | Tidak | Tertunda | Draf |
Replication R-25
- Efek asli
- 0.4 SD
- Efek replikasi
- 0.2 SD
- Putusan
- Lebih kecil, tanda sama
- Diterbitkan
- dengan data dan kode
Ketersediaan testbed
Gbr.Protocol and replication board: example names and illustrative values, not a record or a live system.
Research protocols: how the risk develops.
Hypotheses, controls and scientific acceptance. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Flexibility becomes bias
When outcomes, exclusions, covariates or stopping rules are chosen after the data are seen, many analyses become possible and the most striking one tends to be reported. Each choice looks reasonable alone; together they inflate false positives and effect sizes.
Weak controls confound results
A missing control, unblinded assessment or non-random allocation lets something other than the intervention explain the difference. Design flaws cannot be repaired by analysis; they travel into every result and review built on the study.
Underpowered designs mislead twice
Small samples miss real effects, and the effects they do detect tend to be overestimated. Underpowered studies that reach significance seed literatures that later, larger replications cannot match.
Deviations go unreported
Protocols change for good reasons, such as slow recruitment or a safety signal. When a change is not dated, explained and reported, readers cannot tell a justified amendment from outcome switching, and reviews pool what should not be pooled.
How research protocols is modelled, measured and tested.
Model, asumsi, data, dan ketidakpastiannya, dalam bentuk yang akan diperiksa ilmuwan atau insinyur. Strukturnya mengikuti metode yang dipublikasikan. Nilai yang digambar bersifat ilustratif, bukan temuan.
Model, persamaan, dan asumsi
The model structure used for research protocols, the assumptions it makes and how each is tested.
Ri = f(Hi, Ei, Vi, Ci)bahaya, keterpaparan, kerentanan, dan kapasitas penanggulanganEAL = ∑k pk · Lkatas peristiwa k dengan probabilitas tahunan pkxt+1 = A xt + B ut + εtA carries the couplings, u the shock, ε the error| Asumsi | Mengapa ini dibuat | Bagaimana ini diuji |
|---|---|---|
| Bahaya dan eksposur bersifat independen dalam satu peristiwa | Menjaga integral kerugian tetap dapat dihitung | Bandingkan dengan pencocokan kopula pada catatan gabungan |
| Keterkaitan bersifat linear di dekat titik operasi | Membiarkan guncangan merambat melalui A | Uji di luar rentang linear lalu bandingkan |
| Kurva kerentanan dapat dipindahkan antartempat | Kurva lokal jarang tersedia | Validasi terhadap kerugian teramati jika tersedia |
- Masukan
- dataset berversi dengan asal-usul yang tercatat
- Keluaran
- distribusi, bukan angka tunggal
- Kode
- dirilis bersama kartu model dan pengujiannya
- Reproduksi
- data, kode, lingkungan, dan seed yang sama
Protocols are registered before results in every domain.
- KesehatanDalam praktikTrials register protocols following SPIRIT.What a reader can checkRegistration before enrolment
- AirDalam praktikField experiments state hypotheses and methods first.What a reader can checkPre-registration
- PanganDalam praktikAgricultural trials state sites, seasons and treatments.What a reader can checkTrial registry
Protocols feed the seri Bukti Labs. Registered Laporan and EQUATOR guidelines set practice; studies with people follow the Declaration of Helsinki (revised 2024).
- Protocols for review.
- Replication proposals.
Apa yang diukur, dan seberapa baik.
Setiap indikator membawa satuan, frekuensi, jenis sumber di baliknya, dan label bukti yang akan dibawa suatu nilai. Tidak ada nilai yang ditampilkan: sebuah program menyediakannya berdasarkan wewenangnya sendiri.
| Indikator | Unit | Kadensi | Jenis sumber | Label |
|---|---|---|---|---|
| Registration before data collection | percent of studies with a time-stamped registration | tahunan | Trial and study registries | Statistik terbitan |
| Primary outcome consistency | percent of reports matching the registered primary outcome | tahunan | Registry and publication comparison | TERAMATI |
| Sample size justification | percent of protocols with a power or precision rationale | tahunan | Protocol audit | TERAMATI |
| Reporting guideline adherence | percent of applicable checklist items reported | per studi | Assessment against CONSORT, PRISMA, ARRIVE or STROBE | ESTIMASI |
| Protocol amendments | count per study, each with a stated reason | per studi | Registry history and ethics committee records | Statistik terbitan |
| Registered report availability | number of journals offering the format | tahunan | Center for Open Science journal list | DILAPORKAN |
| Results posting timeliness | months from primary completion to posted results | per studi | Trial registries | Statistik terbitan |
| Randomisation and blinding reported | percent of eligible studies | tahunan | Risk-of-bias assessments | ESTIMASI |
Asal bukti.
Set data publik bernama dan catatan kelembagaan, masing-masing dengan kelas lisensinya. Sumber berdasarkan perjanjian hanya digunakan sesuai ketentuannya dan tidak pernah diterbitkan ulang.
| Sumber | Apa yang diberikannya | Kelas lisensi |
|---|---|---|
| OSF Registries (Center for Open Science) | Time-stamped preregistrations and registered report protocols across disciplines | Open, licence per registration |
| ClinicalTrials.gov (US National Library of Medicine) | Registered trials, protocol change history and posted results | Domain publik |
| WHO International Clinical Trials Registry Platform | Search across primary national trial registries | Free, WHO terms of use |
| PROSPERO (NIHR) | Registered protocols for systematic reviews | Free access, terms of use |
| protocols.io | Versioned, citable step-by-step laboratory and field methods | Open, CC BY for public protocols |
| EQUATOR Network library | Reporting guidelines by study design, with extensions | Free access, licence per guideline |
| Crossref metadata | Links between registrations, articles, corrections and funders | Open metadata, no restrictions |
Siapa yang memutuskan, dan apa yang dilayani bukti.
Laboratorium prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.
| Siapa yang memutuskan | Pertanyaannya | Bukti yang dilayani halaman ini |
|---|---|---|
| Research ethics committees and institutional review boards | Whether a protocol’s risks, consent and design justify approval, and whether an amendment needs fresh review | Complete protocol, sample size rationale, amendment history with reasons |
| Journal editors | Whether to accept a registered report in principle, or whether a submitted analysis matches its plan | Time-stamped registration compared line by line with the manuscript |
| Penyandang dana penelitian | Whether a proposal’s design can answer its question before money is committed | Power or precision rationale, control conditions, data management plan |
| Medicines and device regulators | Whether trial evidence was generated under the protocol submitted to them | Registry history, deviation logs, results posting record |
Keluaran yang dihasilkan topik ini
- Protocol templates stating hypotheses, controls, outcomes and analysis plans before data collection
- Registration records with time stamps and version history
- Deviation logs that date and explain every amendment
- Reporting checklists completed against the relevant EQUATOR guideline
What experts ask of any protocol.
- What exactly is the hypothesis, and what result would count against it?
- What is the comparison: a control group, a baseline period, a counterfactual model or a randomised arm?
- Which outcomes are primary, which are secondary, and how will each be measured?
- What sample, duration or number of runs is needed to detect an effect of the size that matters?
- What would make the team stop early, for safety or for futility, and who decides?
- What will be published if the result is null or the experiment fails?
Why experiments drift without a protocol.
Every experiment involves choices: which observations to exclude, which covariates to adjust for, which time window to use. Each choice may be reasonable alone, but when they are made after seeing the data, the number of possible analyses grows quickly and one of them will usually show something. This is the problem methodologists call analytic flexibility, and it is a central reason why published effects often shrink or vanish when repeated.
Interdisciplinary work adds its own drivers. Disciplines differ in what they treat as a control, how they handle missing data and what level of evidence they expect. A hydrologist, an economist and an epidemiologist may each consider a design rigorous by their own standard while disagreeing about what it shows. A protocol forces those differences into the open before work starts.
Incentives matter too. Positive, novel findings are easier to publish and fund, which rewards flexibility and penalises null results. Pre-registration and registered reports are the main structural responses.
Tools protocols draw on, and where they stop.
- 01
Pre-registration
A time-stamped record of hypotheses and analysis plans. It limits post hoc changes but cannot stop a poorly chosen question.
- 02
Power and design analysis
Estimates how much data is needed to detect a meaningful effect, using probabilitas dan statistika. It depends on assumed effect sizes that are often uncertain.
- 03
Causal designs
Randomisation, difference-in-differences, regression discontinuity and instrumental variables from inferensi kausal. Each rests on assumptions that must be stated and, where possible, tested.
- 04
Acceptance criteria
Pre-agreed thresholds for when a method, model or prototype is considered to work. They make success testable but can be gamed if set too loosely.
A protocol cannot make a bad measurement good or fix a biased sample. Deviations from protocol are permitted when justified, but are reported with their reasons.
Cara hal ini dikaji, dan apa yang tidak dapat dinyatakan metodenya.
- 01Probabilitas dan statistikaPerencanaan ukuran sampel dan daya uji · Meta-analisis dengan penilaian biasDiterapkan di sini
- 02Inferensi kausal dan evaluasi dampakUji coba teracak dan peluncuran bertahap · Evaluasi program kuasi-eksperimentalDiterapkan di sini
- 03Kuantifikasi ketidakpastian dan validasi modelAnggaran ketidakpastian pengukuran · Analisis sensitivitas model simulasiDiterapkan di sini
- 04Rekayasa sistemKetertelusuran dari persyaratan hingga verifikasi · Tinjauan kesiapan per tahapDiterapkan di sini
Where this page’s references lead.
Badan dan dokumen yang menjadi acuan halaman ini. Status dan edisi berubah; setiap tautan menuju badan penerbitnya.
Tanya jawab.
What is the difference between a preregistration and a registered report?
Does preregistration forbid exploratory analysis?
Which reporting guideline applies to my study?
Can a protocol be changed after registration?
Is pre-registration required for every Labs study?
Can a protocol change during a study?
Who writes the protocol?
Kontribusikan bukti dari halaman ini.
Reports is the Consortium’s quarterly publication. What you know about this subject can become evidence, a case or a correction in the next edition, credited to you and published under CC BY 4.0 where it is your own work.
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Bawa metode, dataset, atau pertanyaan.
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