离散多元分析:以1871年加拿大人口普查为例

IF 1.6 2区 历史学 Q1 HISTORY Historical Methods Pub Date : 1983-07-01 DOI:10.1080/01615440.1983.10594104
M. Ornstein
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引用次数: 1

摘要

本文给出了一个应用现代统计方法分析历史数据多变量列联表的实例。这个例子涉及按省份、户主职业和家庭类型分列的城市化的四方交叉表,使用的数据来自加拿大1871年人口普查的个人记录。在将离散多变量分析应用于所选示例之前,首先介绍离散多变量分析的概述。(注释)
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Discrete multivariate analysis: an example from the 1871 Canadian census
An example of the application of modern statistical methods to the analysis of multivariate contingency tables of historical data is presented. The example involves a four-way cross-tabulation of urbanization by province by occupation of head of household by household type using data from individual records from the 1871 census of Canada. An overview of discrete multivariate analysis is first presented before it is applied to the example selected. (ANNOTATION)
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来源期刊
Historical Methods
Historical Methods Multiple-
CiteScore
3.20
自引率
7.10%
发文量
13
期刊介绍: Historical Methodsreaches an international audience of social scientists concerned with historical problems. It explores interdisciplinary approaches to new data sources, new approaches to older questions and material, and practical discussions of computer and statistical methodology, data collection, and sampling procedures. The journal includes the following features: “Evidence Matters” emphasizes how to find, decipher, and analyze evidence whether or not that evidence is meant to be quantified. “Database Developments” announces major new public databases or large alterations in older ones, discusses innovative ways to organize them, and explains new ways of categorizing information.
期刊最新文献
A New Strategy for Linking U.S. Historical Censuses: A Case Study for the IPUMS Multigenerational Longitudinal Panel. Simple Strategies for Improving Inference with Linked Data: A Case Study of the 1850-1930 IPUMS Linked Representative Historical Samples. Reconstruction of Birth Histories for the Study of Fertility in the United States, 1830-1910. Introduction to Special Issues on Historical Record Linking. Linking the 1940 U.S. Census with Modern Data.
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