Table 3.

Regression coefficients and descriptive statistics of significant predictors in the word-understanding analysis.

predictor	coef	exp(coef)	IQR	90-10R	p value
total frequency.c	0.4781	1.6129	2.56	3.85	.0000
isolated freq. (nouns)	0.5654	1.7602	0.00	0.69	.0083
isolated freq. (closed)	0.6830	1.9798	0.00	1.39	.0022
isolated freq. (pred.)	−0.0170	0.9831	0.00	0.69	> .9
MLU.c	−0.0580	0.9437	2.00	4.00	.0725
concreteness.c	0.3531	1.4235	2.00	3.17	.0124
class(closed)	−1.6105	0.1998	na	na	.0387
class(predicate)	−0.2099	0.8107	na	na	> .6

Note. Coef refers to the estimated beta coefficient from the ordinal regression model. Exp(coef) provides the number by which the odds of moving from 00 to 10 or 10 to 11 should be multiplied given an increase of one in the predictor’s value. IQR (interquartile range) is the difference in value between the 75th and 25th percentiles for values of the numerical predictors. 90-10R is like the IQR but uses the 90th and 10th percentiles. These give a sense of how many “increases of one” of the predictor’s value are actually available in the range of the data. The IQR of isolated word frequency is zero because more than 75% of CDI words never occur in isolation.