Concomitant measurements on experimental units or environmental properties are often available at the beginning of an experiment and can be used to reduce residual variance. While blocking factors need to be considered in the design phase, concomitant measurements are introduced as covariates in the analysis stage of an experiment. An analysis of covariance (ANCOVA) model extends the ANOVA resulting from the experiment structure with a regression component that adjusts response values by covariates. We present the construction of ANCOVA models for several experimental designs, develop their Hasse diagrams, and discuss contrast analyses and how they are affected by covariate adjustments. Measured baseline values of the response variable emerge as a special case, and we compare ANCOVA analysis with the popular but inferior change-score analysis to account for baselines.