When the outcome variable is dichotomous, the relationship with the continuous predictor variable is often modeled with alogisticmodel: Pr{Yi=1}=11+e−(a+bxi) where the outcomeYiis coded 0 or 1 for study subjec
Holmes, T.R. (1995). A history of childhood abuse as a predictor variable: implications for outcome research. Research on Social Work Practice, 5, 3, 297-308.Holmes, T.R. (1995). A history of childhood abuse as a predictor variable: Implications for outcome research. Research on Social...
2, No.3, 575·580 On the predictor variable for choice reaction time* GEORGE E. BRIGGS New Mexico State University, Las Cruces, New Mexico 88003 A survey of published research using the Sternberg task was made for the period 1966 to early 1973. A majority of the data are better ...
A factor is a qualitative explanatory variable. Each factor has two or more levels, i.e., different values of the factor. Combinations of factor levels are called treatments. Example: character variable, or a string variable We can't put c
VARIABLE: NAMES = y1-y4 x1 x2; USEVAR ARE y1-y4 x1 x2 x3 x4 ; CLASSES = c(2); AUXILIARY = x1-x2(R3STEP); DEFINE: x3=x1; x4=x2; DATA: FILE IS Math.dat; ANALYSIS: type=mixture; model: %overall% i s |y1@0y2@1y3@2y4@3; ...
a linear combination of relatively few features can be used to predict the outcome or the probability of an outcome. but the sparsity afforded by forward feature selection comes at an unacceptably high cost: forward variable selection (and other variable selection methods) often greatly overfit the...
The primary predictor variable was 5-m gait speed. A well-lit, unobstructed hallway with markings at 0 and 5 m was used for the test. Patients started at the 0-m line and were instructed to walk at a comfortable pace past the 5-m line. Patients were permitted to use an aid such as...
Assumptions of proportional hazard for the final models were evaluated by examining interactions between time and each variable in the model. Interaction terms were included in the model whenever nonproportionality of hazards was observed. For analysis of hospital length of stay, interactions were ...
Chronic comorbidities was a binary variable representing patients with and without ≥1 chronic comorbidity. Adjusted logistic regression was fitted using (1) chronic comorbidities as the outcome and AL quartiles as exposure, and (2) POC as the outcome and AL, chronic comorbidities, and their ...
This random generalized linear model (RGLM) predictor provides variable importance measures that can be used to define a “thinned” ensemble predictor (involving few features) that retains excellent predictive accuracy. Conclusion RGLM is a state of the art predictor that shares the advantages of ...