code: def test_r_glm_baseline_covariates():
      dataset = sm.datasets.get_rdataset("cars").data
      genotype_df = dataset.loc[:, ["speed"]]
      phenotype_df = dataset.loc[:, ["dist"]]
      covariate_df = pd.DataFrame(
          {"intercept": np.ones(genotype_df.shape[0])}
      )
      expected = pd.DataFrame(
          {
              "effect": [3.932409],
              "standard_error": [0.415513],
              "tvalue": [9.46399],
              "pvalue": [1.489836e-12],
              "phenotype": ["dist"],
          }
      )
      baseline = statsmodels_baseline(
          genotype_df, phenotype_df, covariate_df, add_intercept=False
      )
      assert regression_results_equal(expected, baseline)
  
imports: import functions
  import numpy
  import statsmodels.api
  import pandas
  import glow.gwas.functions
  import glow.gwas.lin_reg
  import pytest
label_desc: Use image node_id 8 for calling a global function with example usage: test_r_glm_baseline_covariates() without return types