Becca Winstone learns that her son, Michael, disappears while studying abroad, and it's a race against time when she travels to Europe to track him down. A surprising turn of events reveals just how far one mother will go to protect her family. Exotic locations and thrilling twists will keep you riveted in Missing. How far would you go to save the only thing you have left in the world? At 8 years old, Michael watched as his father, CIA Agent Paul Winstone, was murdered. Now 10 years later, Paul's wife, Becca, is faced with the reality of her son growing up. When Michael is afforded the opportunity to study abroad, his mother reluctantly agrees it's time to let him go. Just a few weeks into his trip Michael disappears, and Becca immediately suspects foul play. When she arrives in Rome, she begins piecing together the clues left behind. It isn't long before the kidnappers realize they've picked a fight with the wrong woman. Becca Winstone has a secret of her own -- before Paul's death, she was also a lethal CIA Agent. But if she wants to find her son alive, Becca will have to rely on old friends and reopen old wounds. Her resourcefulness, skill and determination will be put to the test - but a mother's love knows no limits.

Missing - Netflix

Type: Scripted

Languages: English

Status: Ended

Runtime: 60 minutes

Premier: 2012-03-15

Missing - Missing data - Netflix

In statistics, missing data, or missing values, occur when no data value is stored for the variable in an observation. Missing data are a common occurrence and can have a significant effect on the conclusions that can be drawn from the data. Missing data can occur because of nonresponse: no information is provided for one or more items or for a whole unit (“subject”). Some items are more likely to generate a nonresponse than others: for example items about private subjects such as income. Attrition (“Dropout”) is a type of missingness that can occur in longitudinal studies - for instance studying development where a measurement is repeated after a certain period of time. Missingness occurs when participants drop out before the test ends and one or more measurements are missing. Data often are missing in research in economics, sociology, and political science because governments choose not to, or fail to, report critical statistics. Sometimes missing values are caused by the researcher—for example, when data collection is done improperly or mistakes are made in data entry. These forms of missingness take different types, with different impacts on the validity of conclusions from research: Missing completely at random, missing at random, and missing not at random. Missing data can be handled similarly as censored data.

Missing - Model-based techniques - Netflix

R                      x                          =        0              {\displaystyle R_{x}=0}   and                               R                      y                          =        0              {\displaystyle R_{y}=0}   denote the observed portions of their respective variables.

P        (        X                  |                Y        )              {\displaystyle P(X|Y)}   from complete data and multiplying it by                     P        (        Y        )              {\displaystyle P(Y)}   estimated from cases in which Y is observed regardless of the status of X. Moreover, in order to obtain a consistent estimate it is crucial that the first term be                     P        (        X                  |                Y        )              {\displaystyle P(X|Y)}   as opposed to                     P        (        Y                  |                X        )              {\displaystyle P(Y|X)}  .

P                (                X                ,                Y                )                                                            =                P                (                X                                  |                                Y                )                P                (                Y                )                                                                                                  =                P                (                X                                  |                                Y                ,                                  R                                      x                                                  =                0                ,                                  R                                      y                                                  =                0                )                P                (                Y                                  |                                                  R                                      y                                                  =                0                )                                                          {\displaystyle {\begin{aligned}P(X,Y)&=P(X|Y)P(Y)\&=P(X|Y,R_{x}=0,R_{y}=0)P(Y|R_{y}=0)\end{aligned}}}  

Missing - References - Netflix