2009/04/01 by Sang‐Il Lee · 23 citations
Economics, Econometrics and Finance · Mathematics · Medicine · Psychology · #Algorithm #Association (psychology) #Computer science #Data mining #Economic and Environmental Valuation #Mathematics #Measure (data warehouse) #Medicine #Psychology #Randomization #Randomized controlled trial #Regional Economics and Spatial Analysis #Resampling #Restricted randomization #Spatial and Panel Data Analysis #Statistical hypothesis testing #Statistics
paper · doi:10.1111/j.1538-4632.2009.00749.x
published in Geographical Analysis 41(2), 221-248 (Wiley)
openalex publication_date 2009/04/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/29
This article establishes a unified randomization significance testing framework upon which various local measures of spatial association are commonly predicated. The generalized randomization approach presented is composed of two testing procedures, the extended Mantel test and the generalized vector randomization test. These two procedures employ different randomization assumptions, namely total and conditional randomization, according to the way in which they incorporate local measures. By properly specifying necessary matrices and vectors for a particular local measure of spatial association under a particular randomization assumption, the generalized randomization approach as a whole yields a reliable set of equations for expected values and variances, which then is confirmed by a Monte Carlo simulation utilizing random permutations.