Localized autocorrelation diagnostic statistic ( LADS) for sociological models:Time-series, network, and geographic data sets  

Oleh:

Nass, Clifford ; Moon, Youngme

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: Sociological Methods & Research (SMR) vol. 25 no. 02 (Nov. 1996), page 223-247.

Ketersediaan

Perpustakaan PKPM Nomor Panggil: S28 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

Lihat Detail Induk

Isi artikel

Regression models in sociology, because they are often based on data sets with a surfeit of variables and an underlying connectivity pattern, pemit the use of unique diagnostic techniques. This article elaborates on the localized autocorrelation diagnostic statistic, LADS, which determines the probability that in a model with N cases, a connected set of size C or more among the E most extreme, same-signed residuals occurred by chance. LADS can suggest variables to be included in a model and can be applied t.o time-series, geographic, group (I. e., cliques, blocks, clusters, and different values on a nominal variable), and network data. Exact formulas for LADS for time-series and grouped data, as well as principles for the robustness of LADS under global autocorrelation, are introduced, and a general algoithm for all data sets of connected cases is presented. Examples demonstrate how LADS can suggest new variables and improve the overall fit of models.

Opini Anda

Klik untuk menuliskan opini Anda tentang koleksi ini!

Kembali