"stepwise analysis" is a correct and usable phrase in written English.
It typically refers to the process of breaking down a problem into smaller components in order to understand and solve it. For example, "We used stepwise analysis to determine the best course of action for our project."
In the first stepwise analysis, both attachment and age, were considered as the independent variables.
Analyses were repeated using forward stepwise analysis to assess the consistency of results.
The final regression results are indicated in Table 5 based on the Forward Stepwise analysis.
The model would likely have at least two significant predictors; thus a Forward Stepwise analysis was used.
The stepwise analysis indicated that the remaining benefit after residual stress relaxation was due to geometry improvement and strain hardening.
In a backward stepwise analysis, the weakest serum predictor contributing least to the prediction of severe hyperkalemia was excluded according to its p value.
Multiple regression equations were formulated using the stepwise analysis method to predict travel speed, implement draught and fuel consumption for mouldboard ploughing on Serdang sandy clay loam soil.
The best CoMSIA model was identified from the stepwise analysis results and the corresponding pharmacophore features derived were used for constructing a pharmacophore hypothesis by the Catalyst program.
We chose to do a stepwise analysis as described in the methods.
This stepwise analysis helped us to narrow our focus to two SNPs associated with both expression and drug cytotoxicity.
All variables that were found to have a statistically significant association were introduced into the multiple regression models using stepwise analysis, with a cut-off point of 0.10.
