Binary time-series-cross-section (BTSCS) observations are likely to violate the independence assumption of the ordinary logit or probit statistical model. When observations are temporally related, the results of an ordinary logit or probit analysis may be misleading. Beck, Katz, and Tucker (1998) provide a simple diagnostic for temporal dependence, and a simple remedy based on the idea that BTSCS data is identical to grouped duration data. This recognition allows logit-oriented BTSCS analysts to use familiar methods to incorporate statistical concepts explicitly designed for temporally dependent data.
Beck, Nathaniel, Katz, Jonathan N., and Richard Tucker (1998). "Taking Time Seriously in Binary Time-Series Cross-Section Analysis." American Journal of Political Science 42(4):1260-1288.