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GCRI · Labs

Protocolos de investigación

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.

01Lienzo

Cómo se desarrolla el trabajo.

sistemas · en torno a este temaIlustrativo

Panel de protocolos y replicación

Research protocols · Labs · Quarter 3

Dos réplicas en ejecuciónGCRI · Labs

Protocolos

PR-378 sensor driftExperimento de campoSíAprobadoEn ejecución
PR-705 AI triageAleatorizadoSíCondicionesConfiguración
PR-694 message recallExperimento de encuestaSíAprobadoCompleto
PR-360 heat exposureCohorteNoPendienteBorrador

Replication R-25

Efecto original
0.4 SD
Efecto de réplica
0.2 SD
Veredicto
Menor, mismo signo
Publicado
con datos y código

Disponibilidad de los bancos de pruebas

Protocol and replication board: the screen’s structure, terms and states for Research protocols.Nombres de ejemplo y valores ilustrativos; un diseño, no un registro ni un sistema en vivo.

Fig.Protocol and replication board: example names and illustrative values, not a record or a live system.

02La pregunta

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.

Mecanismo

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.

Mecanismo

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.

Mecanismo

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.

Mecanismo

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.

03Métodos y evidencia

How research protocols is modelled, measured and tested.

El modelo, sus supuestos, sus datos y su incertidumbre, en la forma en que un científico o un ingeniero los comprobaría. Las estructuras siguen métodos publicados. Los valores representados son ilustrativos, no hallazgos.

Modelo, ecuaciones y supuestos

The model structure used for research protocols, the assumptions it makes and how each is tested.

Riesgo del elemento iRi = f(Hi, Ei, Vi, Ci)amenaza, exposición, vulnerabilidad y capacidad de afrontamiento
Pérdida anual esperadaEAL = ∑k pk · Lksobre los eventos k con probabilidad anual pk
Sistemas acopladosxt+1 = A xt + B ut + εtA carries the couplings, u the shock, ε the error
SupuestoPor qué se haceCómo se prueba
La amenaza y la exposición son independientes dentro de un eventoMantiene manejable la integral de pérdidasComparar con un ajuste de cópula sobre registros conjuntos
Los acoplamientos son lineales cerca del punto de operaciónPermite que las perturbaciones se propaguen a través de APerturbar más allá del rango lineal y comparar
Las curvas de vulnerabilidad se transfieren entre lugaresLas curvas locales rara vez están disponiblesValidar frente a las pérdidas observadas cuando existan
Entradas
conjuntos de datos versionados con procedencia
Resultados
distribuciones, nunca cifras únicas
Código
publicado con la ficha de modelo y las pruebas
Reproducción
mismos datos, código, entorno y semilla
Formulaciones estándar de riesgo y de espacio de estados; los supuestos enumerados son los típicos del método, expuestos para su revisión, no resultados.
Principios rectores FAIR · GO FAIR y FORCE11W3C PROV · World Wide Web ConsortiumOrientación para un tratamiento coherente de las incertidumbres · IPCCCEOS Analysis Ready Data · Comité sobre Satélites de Observación de la Tierra
04In the five domains

Protocols are registered before results in every domain.

05Indicadores

Qué se mide y con qué calidad.

Cada indicador lleva su unidad, su periodicidad, el tipo de fuente que lo respalda y la etiqueta de evidencia que llevaría un valor. No se muestran valores: un programa los aporta bajo su propia autoridad.

IndicadorUnidadCadenciaTipo de fuenteEtiqueta
Registration before data collectionpercent of studies with a time-stamped registrationanualTrial and study registriesEstadísticas publicadas
Primary outcome consistencypercent of reports matching the registered primary outcomeanualRegistry and publication comparisonOBSERVADO
Sample size justificationpercent of protocols with a power or precision rationaleanualProtocol auditOBSERVADO
Reporting guideline adherencepercent of applicable checklist items reportedpor estudioAssessment against CONSORT, PRISMA, ARRIVE or STROBEESTIMADO
Protocol amendmentscount per study, each with a stated reasonpor estudioRegistry history and ethics committee recordsEstadísticas publicadas
Registered report availabilitynumber of journals offering the formatanualCenter for Open Science journal listNOTIFICADO
Results posting timelinessmonths from primary completion to posted resultspor estudioTrial registriesEstadísticas publicadas
Randomisation and blinding reportedpercent of eligible studiesanualRisk-of-bias assessmentsESTIMADO
06Fuentes

De dónde procede la evidencia.

Conjuntos de datos públicos y registros institucionales identificados, cada uno con su tipo de licencia. Las fuentes obtenidas por acuerdo solo se utilizan conforme a sus condiciones y nunca se republican.

FuenteLo que aportaTipo de licencia
OSF Registries (Center for Open Science)Time-stamped preregistrations and registered report protocols across disciplinesOpen, licence per registration
ClinicalTrials.gov (US National Library of Medicine)Registered trials, protocol change history and posted resultsDominio público
WHO International Clinical Trials Registry PlatformSearch across primary national trial registriesFree, WHO terms of use
PROSPERO (NIHR)Registered protocols for systematic reviewsFree access, terms of use
protocols.ioVersioned, citable step-by-step laboratory and field methodsOpen, CC BY for public protocols
EQUATOR Network libraryReporting guidelines by study design, with extensionsFree access, licence per guideline
Crossref metadataLinks between registrations, articles, corrections and fundersOpen metadata, no restrictions
07Decisiones

Quién decide y a qué sirve la evidencia.

Laboratorios prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.

Quién decideLa preguntaEvidencia a la que sirve esta página
Research ethics committees and institutional review boardsWhether a protocol’s risks, consent and design justify approval, and whether an amendment needs fresh reviewComplete protocol, sample size rationale, amendment history with reasons
Journal editorsWhether to accept a registered report in principle, or whether a submitted analysis matches its planTime-stamped registration compared line by line with the manuscript
Financiadores de la investigaciónWhether a proposal’s design can answer its question before money is committedPower or precision rationale, control conditions, data management plan
Medicines and device regulatorsWhether trial evidence was generated under the protocol submitted to themRegistry history, deviation logs, results posting record

Productos que genera este tema

  • 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
08Cuestiones centrales

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?
09Mecanismos y factores impulsores

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.

10Métodos y datos

Tools protocols draw on, and where they stop.

  1. 01

    Pre-registration

    A time-stamped record of hypotheses and analysis plans. It limits post hoc changes but cannot stop a poorly chosen question.

  2. 02

    Power and design analysis

    Estimates how much data is needed to detect a meaningful effect, using probabilidad y estadística. It depends on assumed effect sizes that are often uncertain.

  3. 03

    Causal designs

    Randomisation, difference-in-differences, regression discontinuity and instrumental variables from inferencia causal. Each rests on assumptions that must be stated and, where possible, tested.

  4. 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.

11Métodos

Cómo se estudia y lo que los métodos no pueden decir.

  1. Probabilidad y estadísticaPlanificación del tamaño muestral y la potencia · Metaanálisis con evaluación de sesgosAplicado aquí
  2. Inferencia causal y evaluación de impactoPilotos aleatorizados y despliegues escalonados · Evaluación cuasiexperimental de programasAplicado aquí
  3. Cuantificación de la incertidumbre y validación de modelosPresupuestos de incertidumbre de medición · Análisis de sensibilidad de modelos de simulaciónAplicado aquí
  4. Ingeniería de sistemasTrazabilidad de los requisitos a la verificación · Revisiones de preparación por etapasAplicado aquí
12Where this page’s references

Where this page’s references lead.

Los organismos y documentos con los que se lee esta página. El estado y las ediciones cambian; cada enlace lleva al organismo emisor.

13Preguntas

Preguntas y respuestas.

What is the difference between a preregistration and a registered report?
A preregistration is a time-stamped plan deposited before analysis. A registered report is a journal format in which the plan is peer reviewed and accepted in principle before results exist, so publication does not depend on the outcome.
Does preregistration forbid exploratory analysis?
No. It separates the two. Planned analyses are reported as confirmatory; analyses suggested by the data are reported as exploratory, with that label, so readers can weigh them accordingly.
Which reporting guideline applies to my study?
It depends on the design: CONSORT for randomised trials, SPIRIT for trial protocols, PRISMA for systematic reviews, ARRIVE for animal research, STROBE for observational studies. The EQUATOR Network keeps the current list and extensions.
Can a protocol be changed after registration?
Yes, with a dated amendment and a stated reason, and with fresh ethics review where the change affects participants. What damages credibility is undisclosed change, not change itself.
Is pre-registration required for every Labs study?
It is designed to be the default for confirmatory work. Exploratory work is welcome but is labelled as exploratory, so that its findings are treated as hypotheses rather than conclusions.
Can a protocol change during a study?
Yes, for good reasons such as safety or an unforeseen data problem. Each change is dated, justified and reported alongside the result.
Who writes the protocol?
The research team writes it; a subject reviewer independent of the team is designed to check it before work begins.
serie ReportsContribuir

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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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