> summary(soil.mod1) Df Sum Sq Mean Sq F value Pr(>F) field 14 14.1777 1.01270 0.6906 0.7348 field:section 15 11.7912 0.78608 0.5360 0.8468 Residuals 6 8.7989 1.46648 > > library(nlme) > soil.mod2 <- lme(fixed=porosity ~ 1, random=~1|field/section) > > summary(soil.mod2) Linear mixed-effects model fit by REML Data: NULL AIC BIC logLik 110.5931 116.8145 -51.29654 Random effects: Formula: ~1 | field (Intercept) StdDev: 0.2224424 Formula: ~1 | section %in% field (Intercept) Residual StdDev: 6.477535e-05 0.9725733 Fixed effects: porosity ~ 1 Value Std.Error DF t-value p-value (Intercept) 4.40519 0.1730879 15 25.4506 0 Standardized Within-Group Residuals: Min Q1 Med Q3 Max -2.34410779 -0.53967183 -0.05938249 0.55767516 1.81653361 Number of Observations: 36 Number of Groups: field section %in% field 15 30 > > library(lme4) > soil.mod3 <- lmer(porosity~1+(1|field/section)) > > summary(soil.mod3) Linear mixed model fit by REML Formula: porosity ~ 1 + (1 | field/section) AIC BIC logLik deviance REMLdev 110.6 116.9 -51.3 100.9 102.6 Random effects: Groups Name Variance Std.Dev. section:field (Intercept) 0.000000 0.00000 field (Intercept) 0.049478 0.22244 Residual 0.945901 0.97257 Number of obs: 36, groups: section:field, 30; field, 15 Fixed effects: Estimate Std. Error t value (Intercept) 4.4052 0.1731 25.45 >