Stepwise methods are convenient, but have their limitations. Be aware that because stepwise methods select models based solely upon statistical merit, it may choose predictors that have no practical significance. If you have some experience with the data and have expectations about which predictors are important, you should use that knowledge and eschew stepwise methods. If, however, you have many predictors and no idea where to start, running a stepwise analysis and adjusting the selected model is better than no model at all.