Problem:SLP (Session Long Project) The dataset FEV.sav contains 6 variables:
ID, age in years, FEV=forced expiratory volume in liters, height in inches, sex 0=female, 1=male, and smoke=current smoking s ...there is moreshow problemSLP (Session Long Project) The dataset FEV.sav contains 6 variables:
ID, age in years, FEV=forced expiratory volume in liters, height in inches, sex 0=female, 1=male, and smoke=current smoking status 0=nonsmoker 1=smoker.
The data is on 654 children aged 3-19 who were seen childhood respiratory disease study (CRD study) in East Boston. (Fundamentals of Biostatistics, B. Rosner 1995, fourth edition).
The research question is to find out the association between FEV and age, sex, height, and current smoking status.
Now the research questions is: If the smoking status is covariate whether age, height, and sex will still predicate FEV significantly after controlling for the covariate.
Analyze-->Data Reduction-->Factor, click Descriptives, check univariant descriptive, initial solution and KMO and Bartlett's test; click Extraction, check correlation matrix, unrotated factor solution, screen plot, Eigenvalues over 1; click Rotation, check Varimax.
The solution provides step by step method for the calculation of regression model in SPSS . Formula for the calculation and Interpretations of the results are also included.