Software Review: Hunter-Schmidt Meta-Analysis Programs 1.1

Meta-analysis represents a tremendously important scientific breakthrough that allows researchers to see the ‘‘big picture’’ in a given research area. Previously, researchers were left with only the possibility of narrative literature reviews which were influenced by limited human information processing capabilities (Lipsey & Wilson, 2001). The advent of metaanalysis allows researchers to examine data that have accumulated over years or decades and mathematically cumulate the results. The cumulation process can take into account common research artifacts such as sampling error, range restriction, and measurement unreliability. As such, meta-analysis is a critical method that can be used to summarize what we know in a particular field and achieve further insights by testing theoretical and methodological propositions. Thus, it is one of the most useful tools in the scientific process (though it is not a panacea—see Bobko & Stone-Romero, 1998). Finally, meta-analysis is well accepted in ‘‘micro’’ circles (i.e., human resources and organizational behavior) (e.g., Viswesvaran & Ones, 1995) and is becoming more prevalent in ‘‘macro’’ circles (i.e., strategy) (e.g., Certo, Lester, Dalton, & Dalton, 2006; Dalton, Daily, Certo, & Roengpitya, 2003). One of the most interesting facets of the growing popularity of meta-analysis is that finding good software to conduct analyses is remarkably difficult. Some software contains mathematical errors, other software uses only fixed-interval confidence intervals, and still other programs are cumbersome and cost a substantial amount of money (e.g., $800+). Thus, finding a program that is mathematically correct, user friendly, and robust is a genuine joy to researchers (or at least to ‘‘meta-geeks’’ such as myself). The Hunter-Schmidt (HS) programs represent one such pleasant surprise.