ABSTRACT

Purpose

A literature research conducted in education and agricultural education journals published during a period of 10 years revealed that 98% of the studies used parametric analyses. In general, model assumptions were not tested, and statistical criteria were not followed to apply the parametric approach. The objective of this paper is to persuade researchers to use the most appropriate statistical analysis for their data.

Design/Methodology/approach

We present a case study in agricultural education where a parametric multiple linear regression (MLR) could be applied. A survey was designed to find out how Theory of Planned Behavior and Importance-Performance variables were associated to Behavioral Intent concerning landscape water conservation practices. Although model assumptions were not met, we initially carried out a MLR analysis based on the premise that the results could be reported descriptively if they were double cross-validated successfully.

Findings

The double cross-validation of the MLR was not successful, and model assumptions were not held even though the sample size was large. A quantile regression (QR) model fitted the data well. Theory of Planned Behavior and Importance-Performance variables were good predictors of Behavioral Intent, excepting Attitude.

Practical implications

Researchers must rely on statistical criteria to support decisions regarding the use of parametric or non-parametric procedures.

Theoretical implications

The adherence to best practices in the utilization of statistical procedures must be discussed as an ethical matter in research across all fields of science.

Originality/value

We demonstrate that imposing the Central Limit Theorem to use the MLR model is not the correct criterion to apply a parametric approach. We should use double cross-validation.

中文翻译：

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教育和农业教育研究中的参数统计到非参数统计

摘要

目的

一项为期 10 年发表在教育和农业教育期刊上的文献研究表明，98% 的研究使用了参数分析。一般来说，模型假设没有经过测试，也没有遵循统计标准来应用参数方法。本文的目的是说服研究人员对他们的数据使用最合适的统计分析。

设计/方法论/方法

我们提出了一个农业教育案例研究，其中可以应用参数多元线性回归 (MLR)。一项调查旨在了解计划行为理论和重要性-绩效变量如何与景观节水实践的行为意图相关联。虽然没有满足模型假设，但我们最初进行了 MLR 分析，前提是如果成功进行双重交叉验证，结果可以描述性地报告。

发现

MLR 的双重交叉验证没有成功，即使样本量很大，模型假设也不成立。分位数回归 (QR) 模型很好地拟合了数据。计划行为理论和重要性-绩效变量是行为意图的良好预测指标，态度除外。

实际影响

研究人员必须依靠统计标准来支持有关使用参数或非参数程序的决策。

理论意义

在所有科学领域的研究中，必须将遵守使用统计程序的最佳实践作为伦理问题进行讨论。

原创性/价值

我们证明，将中心极限定理应用于 MLR 模型并不是应用参数方法的正确标准。我们应该使用双重交叉验证。