In a text first published in 1991 and translated into English as “To Stay Alive”, Michel Houellebecq offered self-help advice to aspiring writers. Some of it was general: “Develop in yourself a profound resentment toward life… Ruin your life, but not by much… Be abject, and you will be true… When you provoke in others a mixture of horrified pity and contempt, you will know that you are on the right track.” Other tips were playbook-practical: “The mechanisms of the welfare state (unemployment payments, etc.) should be taken full advantage of… In a general way, you will be tossed back and forth between bitterness and anguish. In both cases, alcohol will help.”
If you leave out the people who didn’t complete the study, you’re excluding the cases where your drug did the worst, making the treatment look better than it actually is. You’ve biased your results.
Avoiding this bias, and doing it well, is surprisingly hard. For a long time, researchers relied on ad hoc tricks, each with their own major shortcomings. But in the 1970s, a statistician named Donald Rubin proposed a general technique, albeit one that strained the computing power of the day. His idea was essentially to make a bunch of guesses about what the missing data could be, and then to use those guesses. This method met with resistance at first, but over the past few decades, it has become the most common way to deal with missing data in everything from population studies to drug trials. Recent advances in machine learning might make it even more widespread.
Frankie is a gorgeous, tender story that manages to be sweeping and grand, while also intimate at the same time. At its heart, it’s the story of two friends, the different paths their lives take and the enduring power of their connection. It’s a pleasure in every way possible.
It is easy to love Griffith Park, with its stunning views and iconic observatory. Same goes for Joshua Tree National Park, drawing millions each year with its transcendent desert views and otherworldly flora. But who will care about the abandoned transit lines, the forgotten alleys, the dusty lots behind barbed-wire fences? Christopher Brown, that’s who. And readers of his essential new book about overlooked urban spaces, “A Natural History of Empty Lots.”