Twenty Dutch Holstein-Friesian families, with a total of 715 sires, were evaluated in a granddaughter experiment design for marker-QTL associations. Five traits—milk, fat and protein yield and fat and protein percent—were analyzed. Across-family analysis was undertaken using multimarker regression principles. One and two QTL models were fitted. Critical values for the test statistic were calculated empirically by permuting the data. Individual trait distributions of permuted test statistics differed and, thus distributions, had to be calculated for each trait. Experimentwise critical values, which account for evaluating marker-QTL associations on all 29 autosomal bovine chromosomes and for five traits, were calculated. A QTL for protein percent was identified in one and two QTL models and was significant at the 1 and 2% level, respectively. Extending the multimarker regression approach to an analysis including two QTL was limited by families not being informative at all markers, which resulted in singularity. Below average heterozygosity for the first and last marker lowered information content for the first and last marker bracket. Highly informative markers at the ends of the mapped chromosome would overcome the decrease in information content in the first and last marker bracket and singularity for the two QTL model.