Consider the multiple testing problem of testing null hypotheses $H_1,...,H_s$. A classical approach to dealing with the multiplicity problem is to restrict attention to procedures that control the familywise error rate ($\mathit{FWER}$), the probability of even one false rejection. But if $s$ is large, control of the $\mathit{FWER}$ is so stringent that the ability of a procedure that controls the $\mathit{FWER}$ to detect false null hypotheses is limited. It is therefore desirable to consider other measures of error control. This article considers two generalizations of the $\mathit{FWER}$. The first is the $k-\mathit{FWER}$, in which one is willing to tolerate $k$ or more false rejections for some fixed $k\geq 1$. The second is based on the false discovery proportion ($\mathit{FDP}$), defined to be the number of false rejections divided by the total number of rejections (and defined to be 0 if there are no rejections). Benjamini and Hochberg [J. Roy. Statist. Soc. Ser. B 57 (1995) 289--300] proposed control of the false discovery rate ($\mathit{FDR}$), by which they meant that, for fixed $α$, $E(\mathit{FDP})\leqα$. Here, we consider control of the $\mathit{FDP}$ in the sense that, for fixed $γ$ and $α$, $P\{\mathit{FDP}>γ\}\leq α$. Beginning with any nondecreasing sequence of constants and $p$-values for the individual tests, we derive stepup procedures that control each of these two measures of error control without imposing any assumptions on the dependence structure of the $p$-values. We use our results to point out a few interesting connections with some closely related stepdown procedures. We then compare and contrast two $\mathit{FDP}$-controlling procedures obtained using our results with the stepup procedure for control of the $\mathit{FDR}$ of Benjamini and Yekutieli [Ann. Statist. 29 (2001) 1165--1188].