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EconomicsTop 10 Best Benefit Cost Analysis Software of 2026
Compare benefit cost analysis software options with modeling features, assumptions, and typical use cases for project teams choosing a fit.
How we ranked these tools
Vendors set the topic, but our editors set the inclusion criteria and the evaluation framework before research starts.
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Framework: Features 40% · Ease 30% · Value 30%
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Stata is the best overall choice for analysts who need coded, reproducible benefit-cost outputs across many scenarios because do-files keep assumptions, estimation, and reporting in one script chain, whereas TreeAge Pro fits decision-modeling work that benefits from influence diagram uncertainty propagation in repeatable runs.
Editor’s top 3 picks
Three quick recommendations before you dive into the full comparison below — each one leads on a different dimension.
Stata
Script-driven analysis using do-files keeps assumptions, estimation, and reporting in one reproducible program chain.
Best for: Fits when analysts need coded, reproducible benefit-cost and decision outputs across many scenarios.
TreeAge Pro
Editor pickInfluence diagram modeling with built-in probabilistic uncertainty propagation for decision, chance, and value nodes.
Best for: Fits when analysts need structured decision modeling with repeatable sensitivity and scenario runs.
GoldSim
Editor pickContainer-based architecture isolates reusable submodels, scenario logic, and reporting elements within one simulation model.
Best for: Fits when analysts need uncertainty-aware infrastructure appraisal models beyond spreadsheet scale.
Comparison Table
Stata
generalStatistical software for data science and analysis.
Script-driven analysis using do-files keeps assumptions, estimation, and reporting in one reproducible program chain.
Stata differentiates with a statistical analysis workflow built around reproducible programs, rather than a dedicated benefit-cost analysis point-and-click app. It supports cost-benefit analysis through modeled quantities, scenario runs, and automated calculations inside do-files.
Built-in estimation and reporting features help translate assumptions into outputs like present values and decision metrics with consistent code. Existing Stata users typically benefit most from keeping the full analysis in one language and documentation chain.
- +Automates end-to-end benefit-cost calculations via do-files
- +Strong estimation and diagnostics for uncertainty-aware results
- +Flexible scenario loops for alternative comparison workflows
- +High-quality tables and export paths for decision reporting
- –Benefit-cost analysis workflows require building templates and scripts
- –Limited native support for Monte Carlo simulation without added structure
- –Collaboration features are weaker than spreadsheet-centric review processes
- –Cross-team governance needs disciplined file management and review
Best for: Fits when analysts need coded, reproducible benefit-cost and decision outputs across many scenarios.
TreeAge Pro
specialistDecision analysis software for cost-effectiveness analysis, budget impact models, and Markov modeling.
Influence diagram modeling with built-in probabilistic uncertainty propagation for decision, chance, and value nodes.
TreeAge Pro supports benefit-cost analysis workflows by building models with decision trees and influence diagrams that link assumptions to outputs like benefit-cost ratio and net present value. It has dedicated features for sensitivity and scenario runs, including Monte Carlo style uncertainty propagation for parameters, measures, and outcomes.
Model results can be visualized as charts and tables, and they can be reported by reusing the same model across alternative comparison and baseline scenario definitions. Compared with spreadsheets, TreeAge Pro enforces model structure through its diagram and evaluation engine, which reduces ambiguity in discounting convention choices and incremental analysis logic.
- +Decision tree and influence diagram modeling connects assumptions to evaluation outputs
- +Uncertainty analysis supports Monte Carlo style runs across selected parameters and outcomes
- +Scenario switching keeps baseline and alternative comparisons inside one model
- +Built-in charting and reporting reuse model results without manual cell recomputation
- –Advanced model building takes longer than setting up an equivalent spreadsheet
- –Interoperability and automation surface are limited compared with general analytics stacks
- –Complex multi-stage workflows can become harder to maintain in large diagrams
- –Some customization needs export or add-on steps instead of direct in-tool extensions
Best for: Fits when analysts need structured decision modeling with repeatable sensitivity and scenario runs.
GoldSim
specialistMonte Carlo simulation software for risk and decision analysis.
Container-based architecture isolates reusable submodels, scenario logic, and reporting elements within one simulation model.
GoldSim supports benefit-cost analysis with time-series inputs, cost and benefit streams, discount rates, and alternative assumptions. Analysts can calculate net present value while modeling delays, failures, dependencies, and operational changes. Excel connections, database functions, and external-code interfaces support data exchange with existing analytical workflows.
The main tradeoff is model-building overhead compared with spreadsheet templates or dedicated calculator software. Infrastructure economists can use GoldSim to compare project alternatives that combine construction schedules, demand uncertainty, maintenance events, and long-term operating outcomes.
- +Native Monte Carlo simulation across time-dependent models
- +Hierarchical containers keep complex models modular
- +Graphical elements expose dependencies and assumptions
- +Excel, database, and external-code interfaces support data exchange
- –Steeper learning curve than spreadsheet-based templates
- –Large models require disciplined container architecture
- –Specialized reports may require export workflows
- –Lacks a dedicated benefit-cost template catalog
Public infrastructure economists
Compare transport project alternatives
Decision-ready project ranking
Environmental remediation teams
Evaluate cleanup investment alternatives
Clearer remediation priorities
Show 1 more scenario
Reliability engineering groups
Assess lifecycle intervention options
Better lifecycle decisions
Failure events, maintenance schedules, replacement costs, and downtime assumptions feed long-horizon investment comparisons.
Best for: Fits when analysts need uncertainty-aware infrastructure appraisal models beyond spreadsheet scale.
XLSTAT
specialistStatistical and data analysis solution for Excel, including simulation and CBA tools.
XLSTAT statistical modules for Excel let scenario and sensitivity style analysis stay inside worksheets used to compute benefits and costs.
XLSTAT is a statistical add-in for Excel that turns benefit-cost analysis into spreadsheet-native models with dedicated statistical workflows. It supports core economic evaluation outputs such as cost-benefit ratio, net present value, and internal rate of return while keeping inputs and assumptions visible in Excel grids.
- +Excel-first modeling keeps inputs traceable in standard spreadsheet workflows
- +Built-in evaluation indicators cover NPV, IRR, and cost-benefit ratio in one toolset
- +Statistical diagnostics and plotting reduce manual rework for uncertainty work
- +Add-in functions and repeatable analysis runs support batch project modeling
- –Excel dependency limits deployment options outside desktop or published workbooks
- –Cross-workbook governance needs manual discipline for version control and approvals
- –Automation hinges on workbook structure, which increases sensitivity to template drift
- –Probabilistic simulation workflows are less guided than dedicated risk platforms
Best for: Fits when teams need Excel-based benefit-cost analysis with statistical tooling and repeatable workbook runs for multiple alternatives.
EViews
generalEconometric and forecasting software for time series analysis and modeling.
Scenario execution and result propagation inside a single EViews project keeps discounted outputs aligned across baseline and alternatives.
EViews delivers benefit-cost analysis through a tightly integrated econometric modeling workflow that couples forecasting outputs with valuation calculations. It supports scenario-driven evaluation using built-in time-series tools, constraint-friendly spreadsheets, and consistent reporting structures for net benefits and discounted cash flows.
- +Integrated time-series modeling and discounted cash flow calculations in one project
- +Scenario switching supports incremental comparisons against baseline assumptions
- +Batch scripting enables repeatable sensitivity runs across many parameter sets
- +Built-in reporting exports keep model outputs consistent across alternatives
- –Less suited to headless API-driven pipelines compared with toolchains built for automation
- –Complex models can become hard to govern without strong internal documentation
- –Customization beyond the built-in workflow often depends on scripting knowledge
- –Probabilistic simulations need careful setup to keep uncertainty definitions consistent
Best for: Fits when analysts run scenario-heavy BCA with time-series forecasts and need repeatable, project-contained reporting.
ModelRisk
specialistMonte Carlo simulation Excel add-in for risk analysis and decision making.
Excel-native dependency modeling combines fitted distributions, correlations, and copulas within existing worksheet calculations.
ModelRisk keeps the working model inside Excel, so analysts can reuse existing formulas, named ranges, charts, and financial schedules. The add-in provides probability distributions, correlation structures, distribution fitting, scenario analysis, sensitivity charts, and VBA automation for repeatable runs.
- +Excel-native modeling preserves existing financial formulas and reporting layouts
- +Broad probability distribution library supports uncertain cost and benefit inputs
- +Dependency modeling handles correlated assumptions and linked risk drivers
- +VBA automation supports repeatable simulations and batch analysis
- –Workbook governance depends on spreadsheet controls rather than a dedicated application repository
- –No dedicated benefit-cost workflow for policy templates or results frameworks
- –Complex dependency structures require specialist Excel modeling skills
- –Large workbooks can require careful design to maintain simulation speed
Public-sector appraisal teams
Uncertain infrastructure investment appraisal
Probabilistic investment results
Corporate capital planning teams
Project alternative comparison
Risk-adjusted project ranking
Show 1 more scenario
Consulting analysts
Client scenario and uncertainty studies
Repeatable client analysis
Consultants automate repeated simulations across client workbooks and present sensitivity charts alongside base-case calculations.
Best for: Fits when analysts need probabilistic benefit-cost models built around existing Excel workbooks.
Deltek Acumen Risk
enterpriseProject risk analysis and management software for cost and schedule risk.
Scenario-based risk quantification that propagates risk driver assumptions into discounted benefit-cost outputs.
Deltek Acumen Risk calculates quantified risk impacts for benefit-cost analysis studies by linking scenario data to discounted cash-flow outcomes. Core workflows center on defining alternatives, discounting conventions, and uncertainty inputs, then generating outputs such as expected net benefits and risk-adjusted comparisons.
- +Risk-to-cash-flow linkage keeps assumptions attached to discounted outcomes
- +Reusable scenario libraries speed repeat runs across alternative comparison cycles
- +Traceability supports review of input changes across study iterations
- +Sensitivity and uncertainty outputs fit decision meetings and model QA
- –Requires disciplined setup of risk drivers, units, and scenario structure
- –Spreadsheet-like ad hoc exploration is slower than dedicated numeric workbooks
- –Automation surface is more limited than tools that expose full calculation APIs
- –Complex projects can demand governance to prevent assumption drift
Best for: Fits when benefit-cost analysis teams need repeatable risk quantification tied to discounted outputs.
SAS/ETS
enterpriseAdvanced analytics for forecasting and econometric modeling.
Benefit cost analysis execution is tied to SAS program artifacts, enabling versioned, repeatable scenario runs and controlled outputs.
SAS/ETS provides end-to-end benefit cost analysis workflows built around SAS analytics and economics modeling. It supports scenario comparison, discounting, and investment appraisal metrics using scripted analysis and repeatable project structure.
- +Scripted analysis makes discounting and scenarios reproducible across projects
- +ETL-ready SAS workflow fits multi-source data pipelines for cost and benefit inputs
- +Automation via batch execution supports scheduled re-runs of analyses
- +Strong integration path with broader SAS governance controls and scheduling
- –Workflow setup depends on SAS project conventions and maintained code assets
- –Interactive modeling feels heavier than spreadsheet-centric benefit cost analysis
- –Advanced uncertainty methods require SAS coding and careful distribution choices
- –Scenario results management can become complex without a clear folder structure
Best for: Fits when analysts need repeatable, governed benefit cost analysis with scripted scenarios and scheduled re-runs.
@RISK
enterpriseExcel add-in for Monte Carlo simulation and risk analysis.
Native Excel formula integration with correlated stochastic inputs and linked percentile outputs.
@RISK lets analysts attach probability distributions to workbook cells, correlate related variables, and run Monte Carlo simulation without moving calculations into a separate modeling environment. Its sensitivity analysis views, percentile outputs, tornado charts, and distribution fitting tools support review of uncertain costs and benefits. Excel formulas can calculate net present value, annual cash flows, and comparison metrics while @RISK supplies the stochastic layer.
- +Native Excel integration preserves existing formulas, charts, and workbook structures.
- +Distribution fitting converts historical observations into candidate probability inputs.
- +VBA automation supports repeatable simulation runs and result extraction.
- +Correlation controls represent dependencies between uncertain model inputs.
- –Benefit-cost formulas and reporting templates remain user-built in Excel.
- –Large linked workbooks can produce slow recalculation and result management.
- –Complex macros require disciplined workbook governance and testing.
- –Outputs depend on defensible distribution and correlation assumptions.
Public sector analysts
Transport appraisal models
Range-based investment decisions
Capital planning teams
Infrastructure investment screening
Ranked project scenarios
Show 1 more scenario
Risk consultants
Client model reviews
Repeatable client analyses
Consultants use VBA-controlled runs to produce repeatable outputs across assumptions, scenarios, and workbook versions.
Best for: Fits when appraisal teams need probabilistic analysis inside established Excel financial models.
Analytic Solver
enterpriseExcel-based predictive analytics, simulation, and optimization.
Incremental scenario comparison with appraisal-style KPIs like NPV and benefit-cost ratio in a spreadsheet workflow.
Analytic Solver performs benefit cost analysis workflows with spreadsheet-style inputs for scenarios, discounting, and summary KPIs like benefit cost ratio and net present value. It supports incremental comparisons across baseline and alternative runs so teams can track how assumptions change the outcome.
- +Scenario runs make baseline versus alternative comparisons straightforward
- +Discounting and NPV style outputs fit economic evaluation workflows
- +Spreadsheet-oriented inputs reduce friction for cost tables
- +Incremental analysis supports tracking deltas across assumptions
- –Less automation breadth for batch sensitivity studies than general modeling stacks
- –Collaboration controls are not the primary strength versus governance-first tools
- –Export and integration options can feel spreadsheet-centric rather than API-native
- –Complex probabilistic modeling needs more manual structuring
Best for: Fits when appraisal teams need repeatable scenario and discounting outputs without building custom models.
Conclusion
After evaluating 10 benefit cost analysis software, Stata stands out as our overall top pick — it scored highest across our combined criteria of features, ease of use, and value, which is why it sits at #1 in the rankings above.
Use the comparison table and detailed reviews above to validate the fit against your own requirements before committing to a tool.
How to Choose the Right Benefit Cost Analysis Software
Teams using benefit cost analysis software usually need a workflow that keeps discounting logic tied to assumptions across baseline versus alternative comparison cycles. This buyer's guide covers GoldSim, @RISK, ModelRisk, SAS/ETS, Stata, and spreadsheet-focused options like Excel-linked modeling with Analytic Solver and XLSTAT.
Some stacks keep uncertainty inside familiar spreadsheets through native Excel integrations in @RISK and ModelRisk. Other stacks center on governed, repeatable scenario execution through scripted artifacts in SAS/ETS and do-files in Stata, or through project-contained scenario switching in EViews and decision-graph modeling in TreeAge Pro.
Benefit Cost Analysis Software for discounted, uncertainty-aware evaluation models
Benefit cost analysis software supports discounted evaluation outputs such as present values of benefits and costs, then uses scenario definitions to compare baseline and alternative cases. Many tools also add uncertainty analysis so analysts can propagate risk driver assumptions into discounted outcomes instead of relying on single-point estimates.
GoldSim structures uncertainty-aware modeling in container-based architecture that separates reusable submodels, scenario logic, and reporting elements within one simulation model. @RISK keeps probabilistic inputs inside existing Excel financial models through native formula integration, with linked percentile outputs that stay attached to workbook calculations.
Category-specific evaluation criteria for benefit cost analysis workflows
Benefit cost analysis software must keep discounting and scenario logic attached to the same assumptions used for baseline versus alternative comparison cycles. Tools that separate model components and run uncertainty propagation against those components reduce the chance that results drift from the narrative in project documents.
Teams also need an integration surface that fits the way economic models are built today. Excel-native stacks like @RISK, ModelRisk, Analytic Solver, and XLSTAT matter when spreadsheets already hold formulas, charts, and reviewers’ sanity checks. Script-driven stacks like SAS/ETS and Stata matter when reproducible program artifacts and scheduled re-runs reduce manual change risk.
Uncertainty propagation tied to discounted outcomes
GoldSim runs Monte Carlo simulation across time-dependent models so probability outcomes stay aligned with discounted cash flows. TreeAge Pro propagates uncertainty through influence diagram nodes so decision and value nodes connect to evaluation outputs, not just parameter ranges.
Scenario comparison that matches appraisal KPIs
Analytic Solver supports scenario runs that produce appraisal-style KPIs like NPV and benefit-cost ratio inside spreadsheet workflows. Deltek Acumen Risk ties risk driver assumptions into discounted benefit-cost outputs through reusable scenario libraries.
Excel-native integration for probabilistic models
@RISK embeds probabilistic inputs via native Excel formula integration and outputs linked percentiles. ModelRisk combines fitted distributions, correlations, and copulas with Excel worksheet calculations to preserve existing workbook structures.
Governed reproducibility via code artifacts
SAS/ETS ties benefit cost analysis execution to SAS program artifacts so discounting and scenarios can be repeated with versioned code assets. Stata keeps assumptions, estimation, and reporting in one reproducible program chain using do-files.
Project-contained scenario management for repeatable reporting
EViews keeps scenario execution and result propagation inside a single project so discounted outputs remain aligned across baseline and alternatives. Deltek Acumen Risk uses scenario-based risk quantification that propagates driver assumptions into discounted outputs through structured scenario objects.
Modular model architecture for complex reuse
GoldSim uses a container-based architecture that isolates submodels, scenario logic, and reporting elements inside one simulation model. GoldSim also supports uncertainty-aware reuse patterns that spreadsheet templates often handle through copy and paste rather than modular containers.
Decision framework for selecting Benefit Cost Analysis Software
Start by matching how the organization builds models today. Excel-first teams often choose @RISK, ModelRisk, Analytic Solver, or XLSTAT to preserve workbook formulas and reviewer familiarity while adding probabilistic inputs.
Then decide how governance should work during scenario iterations. Code-first teams often choose SAS/ETS or Stata to keep scenarios repeatable through scripted artifacts, while model-centric teams often choose GoldSim or EViews to keep scenario logic inside a single modeling environment.
Pick the execution philosophy based on where assumptions live
Choose @RISK or ModelRisk when assumptions already live in Excel workbooks and probabilistic inputs must plug into existing worksheet calculations. Choose SAS/ETS or Stata when assumptions and discounting logic should be controlled through versioned code assets and do-files rather than spreadsheet edits.
Choose the way baseline and alternative comparisons are produced
Pick Analytic Solver or EViews when scenario switching needs to produce appraisal-style KPIs and discounted outputs repeatedly with consistent reporting structure. Pick Deltek Acumen Risk when the organization wants risk drivers to remain attached to scenario objects that feed directly into discounted benefit-cost outputs.
Validate uncertainty depth against the model shape
Choose GoldSim when uncertainty must propagate through time-dependent components using Monte Carlo simulation with modular reuse via containers. Choose TreeAge Pro when the decision structure resembles influence diagrams and requires built-in probabilistic propagation across decision, chance, and value nodes.
Assess integration and automation constraints for how work scales
Choose Excel-native tools like @RISK, ModelRisk, or XLSTAT when throughput depends on workbook iteration and linked outputs. Choose SAS/ETS or Stata when batch sensitivity studies must run from scripted artifacts without relying on interactive spreadsheet sessions.
Plan for governance and documentation workload
Choose GoldSim when modular containers can reduce documentation drift by keeping scenario logic and reporting elements organized inside one simulation model. Choose ModelRisk and XLSTAT when workbook governance depends on spreadsheet controls and manual version control discipline across workbooks.
Who benefits from Benefit Cost Analysis Software
Teams that run discounted evaluations repeatedly across baseline and alternative cases need software that keeps discounting logic and assumptions synchronized as scenarios change. Those teams also need uncertainty handling that supports probabilistic propagation into discounted outputs, not just parameter browsing.
The best fit depends on whether the organization centers modeling in Excel workbooks, in scripted code artifacts, or in a dedicated modeling environment with scenario containers and project objects.
Appraisal teams running probabilistic analysis inside existing Excel financial models
These teams benefit from @RISK because it preserves native Excel formula structures while producing linked percentile outputs. ModelRisk supports the same workbook-centric workflow by combining fitted distributions and copulas with worksheet calculations.
Economic evaluation teams that must make scenario runs repeatable through code and schedules
SAS/ETS fits organizations that want discounting and scenarios driven by SAS program artifacts for reproducible reruns. Stata fits teams that need do-files so assumptions, estimation, and benefit-cost outputs stay in one program chain.
Infrastructure or systems analysts building uncertainty-aware infrastructure appraisals with modular reuse
GoldSim fits when complex models need container-based architecture so submodels and reporting elements can be reused across alternative scenarios. EViews fits when scenario execution and discounted output propagation must remain within a single project container.
Decision analysts modeling structured choices with explicit influence relationships
TreeAge Pro fits when decision trees and influence diagrams must connect decision, chance, and value nodes to evaluation outputs. This setup supports uncertainty analysis that runs across selected parameters and outcomes tied to the decision graph.
Risk quantification teams translating risk driver assumptions into discounted benefit-cost results
Deltek Acumen Risk fits when risk driver assumptions must be propagated into discounted benefit-cost outputs through reusable scenario libraries. This approach keeps risk driver and discounted result linkage attached to scenario structure.
Common pitfalls when buying Benefit Cost Analysis Software
Misalignment between the modeling workflow and the tool’s execution model creates downstream rework during scenario iterations. These pitfalls usually appear when teams choose a spreadsheet-centric tool but need heavy automation and governance, or when they choose a scripted tool but still expect interactive exploration as the primary workflow.
Another frequent failure comes from treating uncertainty handling as parameter ranges instead of a structured propagation into discounted outputs. Several tools make that propagation either first-class inside the modeling environment or second-class through spreadsheet discipline, which changes how mistakes show up under review.
Selecting an Excel-native tool and underestimating governance limits across large linked workbooks
@RISK and XLSTAT can keep probabilistic modeling inside workbook workflows, but large linked workbooks can become slow and result management can get fragile. ModelRisk keeps governance dependent on spreadsheet controls rather than a dedicated application repository, so workbook version control discipline must be planned.
Assuming scenario repeatability without tying it to executable artifacts
SAS/ETS and Stata support reproducibility through scripted analysis artifacts and do-files, which reduce manual drift. Spreadsheet-first stacks can still repeat scenarios, but benefit-cost formulas and reporting templates often remain user-built inside Excel rather than governed as packaged scenario templates.
Building complex time-series discounting models without matching the tool’s project structure
EViews keeps time-series modeling and discounted cash flow calculations aligned inside one project, which helps when scenario switching must remain consistent. If the modeling plan depends on modular reuse of submodels and reporting elements, GoldSim’s container architecture supports that reuse more naturally than copy-based spreadsheet templates.
Treating uncertainty handling as a side calculation instead of a propagation into decision metrics
GoldSim and TreeAge Pro propagate uncertainty through structured modeling elements so discounted outcomes reflect probability distributions. Deltek Acumen Risk links risk driver assumptions into discounted benefit-cost outputs through scenario structure, while Excel-only statistical add-ins require stronger workflow discipline to keep uncertainty propagation consistent.
Ignoring how automation and batch throughput affects sensitivity studies
@RISK and ModelRisk can work inside workbook workflows, but batch sensitivity throughput can depend on how linked workbooks are managed. SAS/ETS and Stata handle scripted scenario chains for repeatable runs across many scenarios more directly than interactive desktop workflows.
How analysts validated these Benefit Cost Analysis Software picks
Analysts pulled the category figures from the original publication passages that describe benefit cost analysis software capabilities. Analysts copied each figure beside the passage that states it and then compared that figure with official documentation and the vendor changelog.
Analysts also used an independent review when one was cited alongside the original figure, and they kept a figure only when it matched the documented behavior. A published benchmark was included only when the benchmark itself was the cited source for that specific claim.
Frequently Asked Questions About Benefit Cost Analysis Software
How does @RISK handle uncertainty when benefit and cost logic already sits in Excel?
When should teams pick GoldSim over a spreadsheet add-in like XLSTAT for infrastructure-style scenarios?
Which tool is better for scenario comparison that stays inside a single coded workflow?
What breaks if an organization tries to migrate Excel-based governance to a governed batch environment like SAS/ETS?
How do integrations and APIs affect data flow for benefit cost analysis tools?
How do SSO and RBAC expectations map when multiple analysts share model artifacts?
How does Deltek Acumen Risk support audit traceability during iterative benefit-cost updates?
What is the tradeoff between decision-diagram modeling in TreeAge Pro and spreadsheet-style incremental analysis in Analytic Solver?
Which tool is better for teams that need influence-diagram uncertainty propagation with structured nodes?
Tools reviewed
Primary sources checked during evaluation.
Referenced in the comparison table and product reviews above.
Funding and competing interests
This study was co-funded by several of the vendors assessed in it. No single vendor funded it. Funders could propose the market studied.
They had no role in selecting vendors, setting or weighting criteria, analysing data or drawing conclusions, and they received the same factual-accuracy check as every other vendor assessed.
Market definition, inclusion rules and criteria weights were fixed by an editor before research began and did not change afterwards. Editorial process →
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