Cleophas, Ton J.
SPSS for Starters and 2nd Levelers [M]. -- 2da. ed. -- Switzerland : Springer International Publishing, 2016

Continuous outcome data -- One-sample continuous data (one-sample T-Test, one-sample wilcoxon signed rank test, 10 patients) -- Paired continuous data with predictors (generalized linear models, 50 patients) -- Unpaired continuous data (unpaired T-Test, mann-whitney, 20 patients) -- Linear regression (20 patients) -- Multiple linear regression (20 patients) -- Automatic linear regression (35 patients) -- Linear regression with categorical predictors (60 patients) -- Repeated measures analysis of variance, Friedman (10 patients) -- Repeated measures analysis of variance plus predictors (10 patients) -- Doubly repeated measures analysis of variance (16 patients) -- Repeated measures mixed-modeling (20 patients) -- Unpaired continuous data with three or more groups (one way analysis of variance, Kruskal-Wallis, 30 patients) -- Automatic nonparametric testing (30 patients) -- Trend test for continuous data (30 patients) -- Multistage regression (35 patients) -- Multivariate analysis with path statistics (35 patients) -- Multivariate analysis of variance (35 and 30 patients) -- Missing data imputation (35 patients) -- Meta-regression (20 and 9 studies) -- Poisson regression for outcome rates (50 patients) -- Confounding (40 patients) -- Interaction, random effect analysis of variance (40 patients) -- General loglinear models for identifying subgroups with large health risks (12 populations) -- Curvilinear estimation (20 patients) -- Loess and spline modeling (90 patients) -- Monte Carlo tests for continuous data (10 and 20 patients) -- Artificial intelligence using distribution free data (90 patients) -- Robust testing (33 patients) -- Nonnegative outcomes assessed with gamma distribution (110 patients) -- Nonnegative outcomes assessed with tweedie distribution (110 patients) -- Validating quantitative diagnostic tests (17 patients) -- Reliability assessment of quantitative diagnostic tests (17 patients) -- Binary outcome data -- One-sample binary data (one-sample Z-test, binomial test, 55 patients) -- Unpaired binary data (Chi-square test, 55 patients) -- Logistic regression with a binary predictor (55 patients) -- Logistic regression with a continuous predictor (55 patients) -- Logistic regression with multiple predictors (55 patients) -- Logistic regression with categorical predictors (60 patients) -- Trend tests for binary data (106 patients) -- Paired binary (McNemar test) (139 general practitioners) -- Paired binary data with predictor (139 general practitioners) -- Repeated measures binary data (Cochran’s Q Test), (139 patients) -- Multinomial regression for outcome categories (55 patients) -- Random intercept for categorical outcome and predictor variables (55 patients) -- Comparing the performance of diagnostic tests (650 and 588 patients) -- Poisson regression for binary outcomes (52 patients) -- Ordinal regression for data with underpresented outcome categories (450 patients) -- Probit regression, binary data as response rates (14 tests) -- Monte Carlo tests for binary data (139 physicians and 55 patients) -- Loglinear models, logit loglinear models (445 patients) -- Loglinear models, hierarchical loglinear models (445 patients) -- Validating qualitative diagnostic tests (575 patients) -- Reliability assessment of qualitative diagnostic tests (17 patients) -- Survival and longitudinal data -- Log rank testing (60 patients) -- Cox regression with/without time dependent variables (60 patients) -- Segmented Cox regression (60 patients) -- Assessing seasonality (24 averages) -- Interval censored data analysis for sssessing mean time to cancer relapse (51 patients) -- Polynomial analysis of circadian rhythms (1 patient with hypertension) -- Index
ISBN: 9783319205991

1. MATEMÁTICAS; 2. ANÁLISIS DE DATOS; 3. PROCESAMIENTO DE DATOS; 4. ESTADÍSTICA I. Zwinderman, Aeilko H.

(1) Inv.: 00007814 S.T.: 762.zip