Context. A lot of photometric data is produced by surveys such as Pan-STARRS, LONEOS, WISE or Catalina. These data are a rich source of information about the physical properties of asteroids. There are several possible approaches for utilizing these data. Lightcurve inversion is a typical method that works with individual asteroids. Our approach in this paper is statistical when we focused on large groups of asteroids like dynamical families and taxonomic classes, and the data were not sufficient for individual models. Aims. Our aim was to study the distributions of shape elongation $b/a$ and the spin axis latitude $beta$ for various subpopulations of asteroids and to compare our results, based on Pan-STARRS1 survey, with statistics previously done using different photometric data (Lowell database, WISE data). Methods. We use the LEADER algorithm to compare the $b/a$ and $beta$ distributions for different subpopulations of asteroids. The algorithm creates a cumulative distributive function (CDF) of observed brightness variations, and computes the $b/a$ and $beta$ distributions using analytical basis functions that yield the observed CDF. A variant of LEADER is used to solve the joint distributions for synthetic populations to test the validity of the method. Results. When comparing distributions of shape elongation for groups of asteroids with different diameters $D$, we found that there are no differences for $D < 25$ km. We also constructed distributions for asteroids with different rotation periods and revealed that the fastest rotators with $P = 0 - 4$ h are more spheroidal than the population with $P = 4 - 8$ h.
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