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At least 289 records · Page 16Linked to original sources
PubMed1984

The inflatable penile prosthesis, reoperation and patient satisfaction: a comparison of statistics obtained from patient record review with statistics obtained from intensive followup search.

Of 179 patients who received the inflatable penile prosthesis 43 per cent have required reoperation, 60 per cent of which were performed for mechanical failure. An attempt to evaluate the adequacy of chart review in assessing current function and patient satisfaction was made by comparing reports obtained by chart review to those obtained by direct patient interview. Results showed that if chart review alone was used malfunction would have been underestimated by 13 per cent and patient satisfaction overestimated by 21 per cent. The importance of direct followup in evaluating patients with the inflatable penile prosthesis is demonstrated.

Adult↗
PubMed2001

Extreme-value statistics of hierarchically correlated variables deviation from Gumbel statistics and anomalous persistence.

We study analytically the distribution of the minimum of a set of hierarchically correlated random variables E1, E2,ellipsis, E(N) where E(i) represents the energy of the ith path of a directed polymer on a Cayley tree. If the variables were uncorrelated, the minimum energy would have an asymptotic Gumbel distribution. We show that due to the hierarchical correlations, the forward tail of the distribution of the minimum energy becomes highly nonuniversal, depends explicitly on the distribution of the bond energies epsilon, and is generically different from the superexponential forward tail of the Gumbel distribution. The consequence of these results to the persistence of hierarchically correlated random variables is discussed and the persistence is also shown to be generically anomalous.

Journal Article↗
PubMedDate not supplied

CAN'T MISS: conquer any number task by making important statistics simple. Part 8. Statistical process control: n, np, c, u control charts.

A p control chart is used to monitor a proportion from a binomial variable that reflects the output of a process. The p control chart is a graph that includes serial sample proportions (p) as the variables of interest, a centerline that represents the overall proportion of the samples (p), and upper control limits (UCLs) and Lower control Limits (LCLs) that represent three standard errors (SEp) above and below the centerline. We use a p control chart to estimate with 99.7% confidence that the population proportion of an output variable was within the interval defined by the UCLs and LCLs during a period of baseline monitoring. We further assume that if the process remains stable, the values of future population proportions will remain between the established control limits. An np control chart simply plots the numerators of the sample proportions as the variables of interest. A u control chart is used to monitor ratios. In u control charts, ratios are quantities in which the numerator can have one or more occurrences in reference to the denominator. A c control chart is analogous to an np control chart in that it graphs the numerators from the ratios.

Confidence Intervals↗
PubMed2003

Lies ... damned lies ... and suicide statistics! 'There are three kinds of lies: lies, damned lies and statistics'. Statement attributed to Disraeli in Mark Twain's Autobiography (1924).

In the absence of any measurable outcome in psychiatry, suicide is now regarded as an outcome measure in Mental Health Services. The National Service Framework (NSF) has set the reduction of the suicide rate by 20 per cent over the next seven years as a national priority. This article will examine how reliable suicide is as an outcome measure.

Humans↗