If I modify your first approach like the following, you can see that the output from the above code and your code is basically same # make a data frame version Mutate(markers = sample(0:1, replace = T, size = 11)) %>%ĭo(fitlm = tidy(lm(markers ~ value, data =. So you have to use set.seed to make it constant for every run like set.seed(123) In the second method, Year was used as independent variable while all the location values were the dependent variable.Īnother thing, you are using sample function to create markers which will give you different outputs for every run. Your values from the first method are not matching with the second method because the first method uses markers as the dependent variable and all the variables in the otm_df were used as the independent variables. In the 'Linear_trend_1.xlsx' file, Year row for each location provides you the slope and the statistic is t statistic. You can use the following code to save the coeff, t statistic, and p-value in excel format library(tidyverse)ĭo(fitlm = tidy(lm(value ~ Year, data =. Linear regression does not give you Z statistic as rightly commented by rather linear regression gives you t statistic. SriTES : 2 2 tbl_df list 12 lm list Class :characterĪfgTES : 2 2 tbl_df list 12 lm list Mode :characterĪny help will be useful. Variable data.Length data.Class data.Mode model.Length model.Class model.Mode termīanTES : 2 2 tbl_df list 12 lm list Length:48

Variable data model term estimate std.error statistic p.valueġ BanTES (Intercept) -236. Write.csv(ols, file.path('E:/',filename = 'ols2.csv'), row.names = TRUE) #to save the results in excel format (not working here for me)Ĭapture.output(summary(ols), file = 'ols.csv' )

Mutate(model = map(data, ~lm(value ~ Year, data =. # read ozone data (I converted to a text file first) I am not getting the z-statistics and p-values, additionally estimates are also incorrect by first method. Additionally, not able to find a method to save the output results in excel format. I could find the coefficients and intercepts from linear regression but unable to find a suitable method to get p-value and z value for respective variable trend.

P value linear regression excel