Data transformations for ANOVA assumption violations in agrarian sciences subfields: a systematic review, simulation study, and practical guidelines

Table 1: Variable description

This table provides a list of variables, along with their respective descriptions, collected during the systematic review of articles in agricultural sciences that employed data transformations to validate variance analysis.

Table 2: Entomology

This database was constructed following the identification, screening, eligibility, and inclusion stages of a systematic literature review of articles within the agricultural sciences, specifically focusing on entomology. The review includes studies that applied data transformations to meet the assumptions of variance analysis, providing insight into how this technique is applied in research within the field.

Table 3: Plant Science

This database was constructed following the identification, screening, eligibility, and inclusion stages of a systematic literature review of articles within the agricultural sciences, specifically focusing on plant science. The review includes studies that applied data transformations to meet the assumptions of variance analysis, providing insight into how this technique is applied in research within the field.

Table 4: Forestry

This database was constructed following the identification, screening, eligibility, and inclusion stages of a systematic literature review of articles within the agricultural sciences, specifically focusing on forestry. The review includes studies that applied data transformations to meet the assumptions of variance analysis, providing insight into how this technique is applied in research within the field.

Table 5: Soil Science

This database was constructed following the identification, screening, eligibility, and inclusion stages of a systematic literature review of articles within the agricultural sciences, specifically focusing on soil science. The review includes studies that applied data transformations to meet the assumptions of variance analysis, providing insight into how this technique is applied in research within the field.