Precision Livestock Farming Technology Adoption and Perception Meta-Analysis Data
by Babatope Akinyemi·Updated 2mo ago
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Description
Five cleaned datasets underpin a systematic review and meta-analysis of technology adoption, acceptance, and perception outcomes in precision livestock farming (PLF). The data, compiled from a corpus of peer-reviewed studies, includes effect-size inputs, variance estimates, and moderator variables like stakeholder group and livestock species. Author Babatope Akinyemi deposited the data and accompanying R code on figshare in April 2026 to promote transparency and reproducibility.
Use Cases
Conducting random-effects meta-analyses based on adoption and acceptance proportions.
Performing moderator meta-regression to analyze the influence of stakeholder group or livestock species.
Testing for publication bias in PLF technology research using Egger's test.
Generating publication-quality forest and funnel plots for research dissemination.
Strengths
Includes five distinct, cleaned datasets covering adoption proportions, acceptance Likert-scale means, acceptance proportions, perception Likert-scale means, and perception proportions.
Provides a self-contained R script implementing restricted maximum-likelihood (REML) random-effects meta-analysis, meta-regression, and publication-bias tests.
Data is structured with moderator variables including stakeholder group, country/region, livestock species, and PLF technology type.
Limitations
Row count is unknown, which may limit suitability assessment.
Column-level documentation is absent; field semantics must be inferred after download.
The dataset size is listed as 0.0 B, indicating a very limited scope or potential metadata issue.
Provenance
Source
Compiled from a corpus of peer-reviewed studies identified through a structured database search.
Collection Method
Systematic review and meta-analysis methodology.
Freshness
Last updated 2026-04-22 06:55:21; freshness should be verified.
Geography
Country/region is included as a moderator variable, but specific global coverage is not stated.
Requires R to execute the provided analytical script for full meta-analysis functionality.