code: def generate_logistic():
      # Number of clusters
      nclust = 100
  
      # Regression coefficients
      beta = np.array([1, -2, 1], dtype=np.float64)
  
      # Covariate correlations
      r = 0.4
  
      # Cluster effects of covariates
      rx = 0.5
  
      # Within-cluster outcome dependence
      re = 0.3
  
      p = len(beta)
  
      OUT = open("gee_logistic_1.csv", "w", encoding="utf-8")
  
      for i in range(nclust):
          n = np.random.randint(3, 6)  # Cluster size
  
          x = np.random.normal(size=(n, p))
          x = rx * np.random.normal() + np.sqrt(1 - rx**2) * x
          x[:, 2] = r * x[:, 1] + np.sqrt(1 - r**2) * x[:, 2]
          pr = 1 / (1 + np.exp(-np.dot(x, beta)))
          z = re * np.random.normal() + np.sqrt(
              1 - re**2
          ) * np.random.normal(size=n)
          u = norm.cdf(z)
          y = 1 * (u < pr)
  
          for j in range(n):
              OUT.write("%d, %d," % (i, y[j]))
              OUT.write(",".join(["%.3f" % b for b in x[j, :]]) + "\n")
  
      OUT.close()
  
file_path: statsmodels/statsmodels/genmod/tests/results/gee_generate_tests.py
imports: import numpy
  from scipy.stats.distributions import norm
label_desc: Use image node_id 1 for calling a global function with example usage: generate_logistic() without return types