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Qtech Solutions team of statistician
have experience in designing and analysing highly complex
clinical trials. They are available to work with our clients
in the study design stages, in interim analysis situations
if needed and in the final statistical analysis and reporting
stages of successfully completed studies. We provide comprehensive
statistical services specifically designed to meet the needs
of your study. Our experienced biostatisticians can design,
perform quantitative analyses, and report on clinical trials
in a broad range of therapeutic areas.
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We offer the
following biostatistics services:
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PK Analysis.
- Sample Size Calculations.
- Study Design Assistance .
- Statistical Analysis Plan.
- Statistical Analysis Programming .
- Final Analysis Report .
- Data Safety Monitoring Board (DSMB)
participation.• Study design, sample size estimation,
randomization
- Protocol development.
- Statistical design.
- Protocol statistical section development.
- Regulatory submission statistical section
development.
- Randomization code generation.
- Statistical analysis plan development.
- Statistical analyses.
- Programming validation
- Meta-analyses.
- Electronic data submissions.
- Hypothesis Testing.
- This covers the scope of testing the
available data and determine the sample size. Various
elements such as probability factor, mean population who
qualify to receive drug are calculated based on null hypothesis
and alternate hypothesis values. In this process we also
determine the p-value (Actual Probability) w.r.t Z –
test statistic value.
- Perform sample tests. Data collection
and validation. Perform t-test distributions using proc
t test using hypothesis value.
- Creating Trial Dataset and performing
statistical summarization using proc univariate, proc
means and trying to understand the correctness and trueness
of the data available for use for analysis and testing.
- One Sample t-test and two-sample t-test
are performed for identifying the probability of determining
the right kind of test samples. One-way ANOVA (Analysis
of Variance) – Compares two or more group means
based on independent samples from each group.
- Two way ANOVA – Simultaneously
analyzing two factors that affect a response and includes
another source of variation – blocking factor. This
is mostly used in clinical trial.
- PROC GLM (General linear model) and PROC
Compare.
- Repeated Measures Analysis :
- Multiple measurements taken from the
same experimental unit.
- Perform f-test – comparison of
response profiles
- PROC MIXED – can handle missing
data more efficiently than GLM.
- PROC GENMOD – uses generalized
estimated equations (GEE) for analyzing repeated measures
datasets that have missing values.
- Linear Regressions:
- PROC GLM (Used for linear regression
analysis using single MODEL variable).
- PROC REG (Used for multiple linear regression
analysis using multiple MODEL variables).
- Wilcoxon Signed – Rank test –
using PROC UNIVARIATE.
- Analysis of covariance using ANOVA.
- Wilcoxon Rank-sum test:
- PROC NPAR1WAY – used to sum of
ranks for either group. Can be used to compute the test
statistic value
- Kruskal Wallis test: proc rank &
proc glm (uses output from proc rank)
- Chi-square test: proc freq
- Fisher’s exact test: comparing
two binomial proportions p1 & p2. Useful for small
cell sizes or extreme proportions
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