实际工程数据与网络调查的建筑缺陷因果关系证明:基于经验数据统计分析的三角剖分方法

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引用次数: 0

摘要

本文旨在通过三角测量技术分析混合法研究中发现的建筑物或建筑缺陷,以最大限度地提高其结果的一致性。在早期,研究的方法论方法包括混合方法选项,包括实际项目缺陷数据的收集和结构化的在线问卷调查。本文采用三角剖分法来提高研究结果的信度和效度。研究结果揭示了实际缺陷变量经验输入和描述性统计缺陷普查之间的强相关性。结果还显示了李克特量表的谷歌表格(LS GF)对实际缺陷的自变量和因变量的响应与统计缺陷普查调查;列出了多个缺陷类别之间的决定性相关因果因素。本文从实际缺陷数据收集和在线普查的统计输入中描述、识别并证明了建筑缺陷贡献因素的关键方面。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Attesting Building Defect Causality Factors of The Actual Project Data and Internet Survey: A Triangulation Method on Empirical Data Statistical Analysis
The paper aims to analyse the findings of the building or the construction defects found from the mix-method research through the triangulation technique to maximise its results consistencies. Early on, the methodology approach for the study involved the mix-method option involving the collection of the actual projects’ defect data and the structured online questionnaires survey. In this paper, a triangulation method was used to increase the credibility and validity of research findings. The findings revealed a strong correlation between actual defect variables empirical input and the descriptive statistical defect census. The results also show the Likert Scale’s Google Form (LS GF) responses on the actual defects independent and dependent variables versus statistical defect census survey; tabulates on decisive co-relation causation factor between the multiple defect categories. The paper describes, identifies, and proved the critical aspect of building defects contribution factors from actual defects data collection and online census's statistical input.
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