SPSS 16.0 Statistical Procedures Companion

By M. Norusis. 2003

468 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/5bee63f780dd08c00403ae3189629a6ba83a5444

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Citations in the corpus

The role of family ownership in international entrepreneurship: exploring nonlinear effects (2012, methodology): “We ran a test of parallel lines to check the validity of this assumption (Norušis 2006).”
Rater (dis)agreement on risk assessment measures in sexually violent predator proceedings: Evidence of adversarial allegiance in forensic evaluation? (2009, unknown): “interpreted (Norusis, 2003).”
Critical success criteria for public-private partnership projects: international experts’ opinion (2017, background): “This indicates the excellent uniformity of responses and reliability of the research instrument (Norusis 2008).”
DO SOME EVALUATORS REPORT CONSISTENTLY HIGHER OR LOWER PCL-R SCORES THAN OTHERS? Findings From a Statewide Sample of Sexually Violent Predator Evaluations (2008, background): “the same evaluator to be correlated (Norusis, 2003).”
Varieties of institutional systems: A contextual taxonomy of understudied countries (2016, methodology): “…appropriate for our study as it is the only type of cluster analysis that uses the log- likelihood measure instead of (squared) Euclidian distance (Norusis, 2008), and converges on the most efficient solution by comparing solutions with different numbers of clusters (Chiu, Fang, Chen, Wang, &…”
Public attitudes to the management of invasive non-native species in Scotland (2007, methodology): “…analysis 153 The influences of socio-demographic variables (e.g. age, gender) on levels of agreement with 154 statements regarding attitudes to conservation and invasive non-native species were tested by 155 backward ordinal regression (using the polytomous universal model (PLUM, Norušis, 2005)).”
Divided Loyalty? An Analysis of Fantasy Football Involvement and Fan Loyalty to Individual National Football League (NFL) Teams (2011, background): “That is, small samples may accumulate high standard errors, and if there are too few responses in relation to the number of variables, it may be impossible to converge on a solution (Nurošis, 2006).”