Sas v9

IBM SPSS V24, SAS V9.4 and GraphPad Prism were used. The distribution of the data was evaluated with Kolmogorov-Smirnov test. Paired t-test for ratios or Wilcoxon test was used to compare neuronal size before and after axotomy. Though some datasets had a normal distribution, most of them did not, therefore, non-parametric tests were used for group comparisons. The distribution of a continuous marker was compared among two or more levels of a factor of interest by using Mann-Whitney test. Correlation analysis was used to analyze relationship between two variables. Change of marker overtime was modeled through random-coefficient models using the MIXED procedure in SAS, where spatial-power of time-lag covariance structure was used to account for the correlation structure among measurements. Similarly, repeated-measures models with variance-components covariance structure were also constructed using the MIXED procedure. To estimate the impact of a given predictor on the likelihood of survival, univariable Logistic regression was used and the significance of the predictor was assessed through both p values and Area Under the curve (AUC). A p < 0.05 is considered significant. Details of statistical methods used for individual experiments can be found in figure legends.

Continuous data were tested across two groups with independent or paired Student’s t test; for three or more groupings, ANOVA or mixed model regression (for matched data) followed by Tukey’s test was used to correct for multiple group comparisons. Residuals were inspected to confirm fit of data, and where outliers were present, data were log-transformed prior to analysis. Data are presented as mean ± SEM. Differences were considered significant where two-tailed p values were < 0.05. SAS v9.4 and GraphPad v7 software were used for analysis. Data are graphed as percent of control (100%), but statistical testing was performed on raw numbers.