@article {altman_mri-based_2012,
	title = {MRI-based clinical trials in relapsing-remitting multiple sclerosis: new sample size calculations based on a longitudinal model},
	journal = {Multiple Sclerosis Journal},
	volume = {18},
	number = {11},
	year = {2012},
	pages = {1600{\textendash}1608},
	abstract = {<p>BACKGROUND: Sample sizes for magnetic resonance imaging (MRI)-based clinical trials in multiple sclerosis (MS) generally assume that lesion counts are reasonably described by the negative binomial (NB) model. OBJECTIVE: This study aimed to assess the appropriateness of the NB model for lesion count data and to provide sample sizes for placebo-controlled, MRI-based clinical trials in relapsing-remitting MS using a more realistic model. METHODS: The fit of the NB model in each arm of five MS clinical trials was assessed using Pearson{\textquoteright}s chi-squared statistic. Required sample sizes associated with various tests of treatment effect were estimated by simulating data from a new, longitudinal model for repeated lesion count data on individual patients. RESULTS: Evidence (p \&lt; 0.05) against the NB model was found in at least one arm of four of the five trials. If a trial is designed using this model but the resulting clinical data do not follow its assumptions then this trial can be seriously under-powered for assessing differences in mean lesion counts. CONCLUSION: Sample sizes based on the longitudinal model are more realistic and often smaller than those previously reported using the NB model.</p>
},
	keywords = {Brain, Chi-Square Distribution, Computer Simulation, Controlled Clinical Trials as Topic, Endpoint Determination, Humans, Longitudinal Studies, magnetic resonance imaging, Models, multiple sclerosis, Predictive Value of Tests, Relapsing-Remitting, Sample Size, Statistical, Time Factors, Treatment Outcome},
	doi = {10.1177/1352458512444326},
	author = {Altman, RM and Petkau, A.John and Vrecko, D and Smith, A}
}
@article {brotto_predictors_2011,
	title = {Predictors of sexual desire disorders in women},
	journal = {The Journal of Sexual Medicine},
	volume = {8},
	number = {3},
	year = {2011},
	pages = {742{\textendash}753},
	abstract = {<p>INTRODUCTION: A historic belief was that testosterone was the "hormone of desire." However, recent data, which show either minimal or no significant correlation between testosterone levels and women{\textquoteright}s sexual desire, suggest that nonhormonal variables may play a key role. AIM: To compare women with hypoactive sexual desire disorder (HSDD) and those with the recently proposed more symptomatic desire disorder, Sexual Desire/Interest Disorder (SDID), on the relative contribution of hormonal vs. nonhormonal variables. METHODS: Women with HSDD (N = 58, mean age 52.5) or SDID (N = 52, mean age 50.9) participated in a biopsychosocial assessment in which six nonhormonal domains were evaluated for the degree of involvement in the current low desire complaints. Participants provided a serum sample of hormones analyzed by gas chromatography-mass spectrometry or liquid chromatography/mass spectrometry/mass spectrometry. MAIN OUTCOME MEASURES: Logistic regression was used to assess the ability of variables (nonhormonal: history of sexual abuse, developmental history, psychosexual history, psychiatric status, medical history, and sexual/relationship-related factors; hormonal: dehydroepiandrosterone [DHEA], 5-diol, 4-dione, testosterone, 5-α-dihydrotestosterone, androsterone glucuronide, 3α-diol-3G, 3α-diol-17G, and DHEA-S; and demographic: age, relationship length) to predict group membership. RESULTS: Women with SDID had significantly lower sexual desire and arousal scores, but the groups did not differ on relationship satisfaction or mood. Addition of the hormonal variables to the two demographic variables (age, relationship length) did not significantly increase predictive capability. However, the addition of the six nonhormonal variables to these two sets of predictors significantly increased ability to predict group status. Developmental history, psychiatric history, and psychosexual history added significantly to the predictive capability provided by the basic model when examined individually. CONCLUSIONS: Nonhormonal variables added significant predictive capability to the basic model, highlighting the importance of their assessment clinically where women commonly have SDID in addition to HSDD, and emphasizing the importance of addressing psychological factors in treatment.</p>
},
	keywords = {Affect, Case-Control Studies, Chi-Square Distribution, Female, Gonadal Steroid Hormones, Humans, Interpersonal Relations, Interviews as Topic, Libido, Logistic Models, Middle Aged, Psychological, Psychological Tests, Sexual Dysfunctions, Surveys and Questionnaires},
	doi = {10.1111/j.1743-6109.2010.02146.x},
	author = {Brotto, Lori A. and Basson, Rosemary and Petkau, A.John and Labrie, Fernand}
}
