Economic analysis of 2 4 factorial agronomic experiments
The 24 factorial experiment has become increasingly popular in on-farm agronomic experimentation, in part due to the efforts of CIMMYT's maize training program. This experiment is used to examine main effects and interactions for four different factors, each of which is set at two levels. If the two levels for each factor are respectively set at the farmer's level and at a high, non-l imiting level, the experiment is useful in identifying those factors that limit crop yield (Palmer et al, 1980). If the levels are respectively set at the farmer's level and at a higher level that appears to be possible for target farmers, the experiment can also serve as a basis for formulating recommendations for farmers. The 24 factorial experiment has been used to study several arrangements of factors (Maize Training Program, 1981), including variety, N level, insect control, density, weed control, timing and placement of Nand P, and so on. However, the very characteristic that makes this experiment useful - the simultaneous testing of multiple factors - creates compl ications in the economic analysis of results. The major compl ication is that not all treatments in a given experiment are necessarily included in the partial budget used in economic analysis. Sometimes data from individual treatments are used in analysis; at . other times averages for main effects are used, depending on the results of statistical analysis. The purpose 6f this note, then, i~ to address this compl.ication and to provide guidel iness for deal ing with it when economic analysis of 24 factorial experiments is to be conducted.
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| Format: | Handbook biblioteca |
| Language: | English |
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CIMMYT
1981
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| Subjects: | AGRICULTURAL SCIENCES AND BIOTECHNOLOGY, CROPPING SYSTEMS, PRICES, STATISTICAL METHODS, YIELD FACTORS, GROSS MARGINS, COST BENEFIT ANALYSIS, FERTILIZER APPLICATION, TILLAGE, ECONOMIC ANALYSIS, BUDGETS, MARGINAL ANALYSIS, |
| Online Access: | http://hdl.handle.net/10883/855 |
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dig-cimmyt-10883-8552021-03-31T14:27:05Z Economic analysis of 2 4 factorial agronomic experiments Harrington, L.W. AGRICULTURAL SCIENCES AND BIOTECHNOLOGY CROPPING SYSTEMS PRICES STATISTICAL METHODS YIELD FACTORS GROSS MARGINS COST BENEFIT ANALYSIS FERTILIZER APPLICATION TILLAGE ECONOMIC ANALYSIS BUDGETS MARGINAL ANALYSIS CROPPING SYSTEMS PRICES STATISTICAL METHODS YIELD FACTORS GROSS MARGINS COST BENEFIT ANALYSIS FERTILIZER APPLICATION TILLAGE ECONOMIC ANALYSIS BUDGETS MARGINAL ANALYSIS The 24 factorial experiment has become increasingly popular in on-farm agronomic experimentation, in part due to the efforts of CIMMYT's maize training program. This experiment is used to examine main effects and interactions for four different factors, each of which is set at two levels. If the two levels for each factor are respectively set at the farmer's level and at a high, non-l imiting level, the experiment is useful in identifying those factors that limit crop yield (Palmer et al, 1980). If the levels are respectively set at the farmer's level and at a higher level that appears to be possible for target farmers, the experiment can also serve as a basis for formulating recommendations for farmers. The 24 factorial experiment has been used to study several arrangements of factors (Maize Training Program, 1981), including variety, N level, insect control, density, weed control, timing and placement of Nand P, and so on. However, the very characteristic that makes this experiment useful - the simultaneous testing of multiple factors - creates compl ications in the economic analysis of results. The major compl ication is that not all treatments in a given experiment are necessarily included in the partial budget used in economic analysis. Sometimes data from individual treatments are used in analysis; at . other times averages for main effects are used, depending on the results of statistical analysis. The purpose 6f this note, then, i~ to address this compl.ication and to provide guidel iness for deal ing with it when economic analysis of 24 factorial experiments is to be conducted. 16 pages 2012-01-06T05:06:03Z 2012-01-06T05:06:03Z 1981 Handbook http://hdl.handle.net/10883/855 English CIMMYT Economics Training Note CIMMYT manages Intellectual Assets as International Public Goods. The user is free to download, print, store and share this work. In case you want to translate or create any other derivative work and share or distribute such translation/derivative work, please contact CIMMYT-Knowledge-Center@cgiar.org indicating the work you want to use and the kind of use you intend; CIMMYT will contact you with the suitable license for that purpose. Open Access PDF Mexico CIMMYT |
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AGRICULTURAL SCIENCES AND BIOTECHNOLOGY CROPPING SYSTEMS PRICES STATISTICAL METHODS YIELD FACTORS GROSS MARGINS COST BENEFIT ANALYSIS FERTILIZER APPLICATION TILLAGE ECONOMIC ANALYSIS BUDGETS MARGINAL ANALYSIS CROPPING SYSTEMS PRICES STATISTICAL METHODS YIELD FACTORS GROSS MARGINS COST BENEFIT ANALYSIS FERTILIZER APPLICATION TILLAGE ECONOMIC ANALYSIS BUDGETS MARGINAL ANALYSIS AGRICULTURAL SCIENCES AND BIOTECHNOLOGY CROPPING SYSTEMS PRICES STATISTICAL METHODS YIELD FACTORS GROSS MARGINS COST BENEFIT ANALYSIS FERTILIZER APPLICATION TILLAGE ECONOMIC ANALYSIS BUDGETS MARGINAL ANALYSIS CROPPING SYSTEMS PRICES STATISTICAL METHODS YIELD FACTORS GROSS MARGINS COST BENEFIT ANALYSIS FERTILIZER APPLICATION TILLAGE ECONOMIC ANALYSIS BUDGETS MARGINAL ANALYSIS |
| spellingShingle |
AGRICULTURAL SCIENCES AND BIOTECHNOLOGY CROPPING SYSTEMS PRICES STATISTICAL METHODS YIELD FACTORS GROSS MARGINS COST BENEFIT ANALYSIS FERTILIZER APPLICATION TILLAGE ECONOMIC ANALYSIS BUDGETS MARGINAL ANALYSIS CROPPING SYSTEMS PRICES STATISTICAL METHODS YIELD FACTORS GROSS MARGINS COST BENEFIT ANALYSIS FERTILIZER APPLICATION TILLAGE ECONOMIC ANALYSIS BUDGETS MARGINAL ANALYSIS AGRICULTURAL SCIENCES AND BIOTECHNOLOGY CROPPING SYSTEMS PRICES STATISTICAL METHODS YIELD FACTORS GROSS MARGINS COST BENEFIT ANALYSIS FERTILIZER APPLICATION TILLAGE ECONOMIC ANALYSIS BUDGETS MARGINAL ANALYSIS CROPPING SYSTEMS PRICES STATISTICAL METHODS YIELD FACTORS GROSS MARGINS COST BENEFIT ANALYSIS FERTILIZER APPLICATION TILLAGE ECONOMIC ANALYSIS BUDGETS MARGINAL ANALYSIS Harrington, L.W. Economic analysis of 2 4 factorial agronomic experiments |
| description |
The 24 factorial experiment has become increasingly popular in on-farm agronomic experimentation, in part due to the efforts of CIMMYT's maize training program. This experiment is used to examine main effects and interactions for four different factors, each of which is set at two levels. If the two levels for each factor are respectively set at the farmer's level and at a high, non-l imiting level, the experiment is useful in identifying those factors that limit crop yield (Palmer et al, 1980). If the levels are respectively set at the farmer's level and at a higher level that appears to be possible for target farmers, the experiment can also serve as a basis for formulating recommendations for farmers. The 24 factorial experiment has been used to study several arrangements of factors (Maize Training Program, 1981), including variety, N level, insect control, density, weed control, timing and placement of Nand P, and so on. However, the very characteristic that makes this experiment useful - the simultaneous testing of multiple factors - creates compl ications in the economic analysis of results. The major compl ication is that not all treatments in a given experiment are necessarily included in the partial budget used in economic analysis. Sometimes data from individual treatments are used in analysis; at . other times averages for main effects are used, depending on the results of statistical analysis. The purpose 6f this note, then, i~ to address this compl.ication and to provide guidel iness for deal ing with it when economic analysis of 24 factorial experiments is to be conducted. |
| format |
Handbook |
| topic_facet |
AGRICULTURAL SCIENCES AND BIOTECHNOLOGY CROPPING SYSTEMS PRICES STATISTICAL METHODS YIELD FACTORS GROSS MARGINS COST BENEFIT ANALYSIS FERTILIZER APPLICATION TILLAGE ECONOMIC ANALYSIS BUDGETS MARGINAL ANALYSIS CROPPING SYSTEMS PRICES STATISTICAL METHODS YIELD FACTORS GROSS MARGINS COST BENEFIT ANALYSIS FERTILIZER APPLICATION TILLAGE ECONOMIC ANALYSIS BUDGETS MARGINAL ANALYSIS |
| author |
Harrington, L.W. |
| author_facet |
Harrington, L.W. |
| author_sort |
Harrington, L.W. |
| title |
Economic analysis of 2 4 factorial agronomic experiments |
| title_short |
Economic analysis of 2 4 factorial agronomic experiments |
| title_full |
Economic analysis of 2 4 factorial agronomic experiments |
| title_fullStr |
Economic analysis of 2 4 factorial agronomic experiments |
| title_full_unstemmed |
Economic analysis of 2 4 factorial agronomic experiments |
| title_sort |
economic analysis of 2 4 factorial agronomic experiments |
| publisher |
CIMMYT |
| publishDate |
1981 |
| url |
http://hdl.handle.net/10883/855 |
| work_keys_str_mv |
AT harringtonlw economicanalysisof24factorialagronomicexperiments |
| _version_ |
1756086313442869248 |