The "Error in lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...) : 0 (non-na) cases" error typically occurs when trying to fit a linear regression model using the
lm() function in R, and it indicates that there are no valid (non-NA) cases in the data that can be used to fit the model. This can happen for a number of reasons, such as:
- The data contains only missing values (NA).
- The data contains a single row or column.
- The predictor variables (x) are all constant or collinear (i.e. highly correlated).
To fix this error, you need to identify the cause of the problem and take appropriate action. Here are some steps you can follow:
- Check for missing values: Use the
is.na()function to check if the data contains any missing values, and use the
na.omit()function to remove rows with missing values.
- Check the dimensions of the data: Make sure that the data has more than one row and column.
- Check for collinearity: Use the
cor()function to compute the correlations between the predictor variables, and remove any variables that are highly correlated. You can also try adding a small amount of noise (jitter) to the data to reduce collinearity.
- Check the model formula: Make sure that the model formula is correctly specified, and that all variables are spelled correctly.