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03073aam a2200373 i 4500 001 441C28C2440211EF98CC15ED37ECA4DB 003 SILO 005 20240717010108 008 230806t20232023enka b 000 0 eng d 020 $a 9781009303385 020 $a 1009303384 020 $a 100945417X 020 $a 9781009454179 035 $a (OCoLC)1392340279 040 $a YDX $b eng $e rda $c YDX $d UKMGB $d AUXAM $d OCLCO $d OCLCQ $d YDX $d GSU $d SILO 050 4 $a BF39.2 A52 C65 2023 100 1 $a Cole, Veronica, $e author. 245 10 $a Algorithms for measurement invariance testing : $b contrasts and connections / $c Veronica T. Cole and Conor H. Lacey. 264 1 $a Cambridge ; $b Cambridge University Press, $c 2023. 300 $a 84 pages : $b illustrations (some color) ; $c 24 cm. 490 1 $a Elements in research methods for developmental science 504 $a Includes bibliographical references. 505 0 $a Algorithms for measurement invariance testing : contrasts and connections -- Latent variable models -- What is measurement invariance? What is DIF? -- Codifying measurement noninvariance and differential item functioning in different latent variable frameworks -- Models for measurement : noninvariance and differential item functioning -- Consequences of measurement : Noninvariance and differential item functioning -- Detecting measurement : Noninvariance and differential item functioning -- Recommendations for best practices. 520 $a "Latent variable models are a powerful tool for measuring many of the phenomena in which developmental psychologists are often interested. If these phenomena are not measured equally well among all participants, this would result in biased inferences about how they unfold throughout development. In the absence of such biases, measurement invariance is achieved; if this bias is present, differential item functioning (IDF) would occur. This Element introduces the testing of measurement invariance/DIF through nonlinear factor analysis. After introducing models which are used to study these questions, the Element uses them to formulate different definition of measurement invariance and IDF. It also focuses on differrent procedures for locating and quantifying this effects. The Element finally provides recommendations for researchers about how to navigate these options to make valid inferences about measurement in their own data." -- $c Publisher's description. 650 0 $a Developmental psychology $x Statistical methods. 650 0 $a Psychometrics $x Statistical methods. 650 0 $a Algorithms. 700 1 $a Lacey, Conor H., $e author. 776 08 $i Electronic version: $a Cole, Veronica T. $t Algorithms for measurement invariance testing. $d Cambridge, United Kingdom ; New York, NY : Cambridge University Press, 2023 $z 9781009303408 $w (OCoLC)1412388286 830 0 $a Cambridge elements. $p Elements in research methods for developmental science. 941 $a 1 952 $l USUX851 $d 20240717023045.0 956 $a http://locator.silo.lib.ia.us/search.cgi?index_0=id&term_0=441C28C2440211EF98CC15ED37ECA4DB 994 $a C0 $b IWAInitiate Another SILO Locator Search