Statistical Hypotheses. No inferences are to be made on the primary effectiveness endpoint; therefore, no hypotheses are formulated.
Statistical Hypotheses. No hypothesis testing of the primary effectiveness endpoint is planned.
Statistical Hypotheses. The null and alternative hypotheses are formulated in terms of the predefined margin of 0.05 for noninferiority: H0: µ(T) – µ(C) ≥ 0.05 Ha: µ(T) – µ(C) < 0.05 where µ(T) and µ(C) denote the mean distance VA for PRECISION1 and Biotrue, respectively, on the logMAR scale.
Statistical Hypotheses. The null and alternative hypotheses are formulated in terms of the predefined margin of 0.10 (10%) for noninferiority. H0: P(T) – P(C) ≤ -0.10 Ha: P(T) – P(C) > -0.10 where P(T) and P(C) denote the proportion of subjects attaining at least 20/20 in CLCDVA at Week 1 Follow-up in each eye (OD and OS) for and Biofinity contact lenses, respectively.
Statistical Hypotheses. The null and alternative hypotheses are formulated in terms of the predefined margin of 0.10 (in logMAR scale) for noninferiority: H0: μ(T) − μ(C) ≥ 0.10 Ha: μ(T) − μ(C) < 0.10 where μ(T) and μ(C) denote the Week 1 Follow-up mean CLCDVA for contact lenses, respectively, on the logMAR scale. and Biofinity
Statistical Hypotheses. The null and alternative hypotheses are formulated in terms of the predefined margin of 1.0 for noninferiority: H0: μ(DACP D) - μ(DACP) ≤ -1.0 Ha: μ(DACP D) - μ(DACP) > -1.0 where μ(DACP D) and μ(DACP) denote the mean overall vision rating for DACP Digital and DACP, respectively.
Statistical Hypotheses. 24 6.4.1.2 Analysis Methods 24 6.4.2 Secondary Effectiveness 24 6.5 Subgroup Analyses 25 6.6 Handling of Missing Data 25 6.7 Multiplicity 25 6.8 Safety Analysis 25 6.9 Interim Analyses 26 26 7 ADVERSE EVENTS AND DEVICE DEFICIENCIES 26 7.1 General Information 28 7.2 Monitoring for Adverse Events 31 7.3 Procedures for Recording and Reporting 32 7.4 Return product analysis 34 7.5 Follow-up of Subjects with Adverse Events 34 7.6 Pregnancy in the Clinical Study 34 8 CONFIDENTIALITY, BIAS, AND MASKING 34 8.1 Subject Confidentiality and Methods Used to Minimize Bias 34 8.2 Unmasking of the Study Treatment 35 9 DATA HANDLING AND ADMINISTRATIVE REQUIREMENTS 35
Statistical Hypotheses. 30 6.4.1.2 Analysis Methods 30 6.6 Handling of Missing Data 32 6.8 Safety Analysis 32 7 ADVERSE EVENTS AND DEVICE DEFICIENCIES 33 7.1 General Information 36 7.2 Monitoring for Adverse Events 39 7.3 Procedures for Recording and Reporting 39
Statistical Hypotheses. 31 6.4.1.2 Analysis Methods 31 6.5 Subgroup Analyses 32 6.6 Handling of Missing Data 32 6.7 Multiplicity 32 6.8 Safety Analysis 32 6.9 Interim Analyses 33 6.10 Sample Size Justification 33 7 ADVERSE EVENTS AND DEVICE DEFICIENCIES 33 7.1 General Information 35 7.2 Monitoring for Adverse Events 38 7.3 Procedures for Recording and Reporting 38 7.4 Return product analysis 40 7.5 Follow-Up of Subjects with Adverse Events 40 7.6 Pregnancy in the Clinical Study 41 8 CONFIDENTIALITY, BIAS, AND MASKING 41 8.1 Subject Confidentiality and Methods Used to Minimize Bias 41 8.2 Unmasking of the Study Treatment 42 9 DATA HANDLING AND ADMINISTRATIVE REQUIREMENTS 42 9.1 Completion of Source Documents and Case Report Forms 42 9.2 Data Review and Clarifications 43 9.3 Regulatory Documentation and Records Retention 43 10 ETHICS AND COMPLIANCE 43 10.1 Compliance 44 10.2 Institutional Review Board (IRB) 44
Statistical Hypotheses. 9.1.1. Primary Hypothesis
