On the application of probability theory to agricultural experiments. Essay on principles. Section 9.¶
Neyman, J. (1990). On the application of probability theory to agricultural experiments. Essay on principles. Section 9.: Essay on principles. Statistical Science, 5(4), 465-472.
Cited by¶
3 citations across 3 artifacts.
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Primes¶
- Blocking (In Experimental Design)
- 3. The within-block randomization preserving unbiasedness — randomization continues within each block (not across the whole sample), maintaining exchangeability and unbiasedness of treatment-group comparisons while leveraging the block structure, so that treatment effects remain causally interpretable
This sourceIntroduces the potential-outcomes / randomization-based framework for unbiased treatment comparisons in agricultural field experiments
- 3. The within-block randomization preserving unbiasedness — randomization continues within each block (not across the whole sample), maintaining exchangeability and unbiasedness of treatment-group comparisons while leveraging the block structure, so that treatment effects remain causally interpretable
- Factorial Design
This sourceTier C (bibliography only): the potential-outcomes / randomization-based foundation of causal inference for agricultural field experiments (originally Roczniki Nauk Rolniczych, 1923).
- Randomization
- 2. The unbiased-estimation guarantee in expectation — across the ensemble of possible randomizations, treatment groups are statistically equivalent on all pre-treatment covariates (both observed and unobserved), permitting valid causal inference from a single realization
This sourceNeyman causal inference randomization-based agricultural experiments probability-theory.
- 2. The unbiased-estimation guarantee in expectation — across the ensemble of possible randomizations, treatment groups are statistically equivalent on all pre-treatment covariates (both observed and unobserved), permitting valid causal inference from a single realization
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