The estimation of treatment effects in observational studies is susceptible to bias due to model misspecification. Corresponding confidence intervals and p-values are moreover overly optimistic when variable selection or regularisation techniques are adopted. We will therefore develop treatment effect estimators which are less sensitive to model specification, along with honest confidence intervals and hypothesis tests.